laser desorption/ionization mass spectrometry for direct

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Laser desorption/ionization mass spectrometry fordirect profiling and imaging of small moleculesfrom raw biological materialsSangwon ChaIowa State University

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Laser desorption/ionization mass spectrometry for direct profiling and imaging of small molecules from raw biological materials

by

Sangwon Cha

A dissertation submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

Major: Analytical Chemistry

Program of Study Committee: Edward S.Yeung, Major Professor

Robert S. Houk Srdija Jeftinija

Victor S.-Y. Lin Basil J. Nikolau Hans Stauffer

Iowa State University

Ames, Iowa

2008

Copyright © Sangwon Cha, 2008. All rights reserved.

3307070

3307070 2008

Copyright 2008 by Sangwon Cha All rights reserved

ii

To My Families and Friends

iii

TABLE OF CONTENTS

ABSTRACT v

CHAPTER 1. GENERAL INTRODUCTION 1

Dissertation Organization 1 Laser Desorption Ionization Mass Spectrometry 1 Laser Desorption Ionization Mass Spectrometry of Small Molecules 3 Imaging Mass Spectrometry of Small Molecules 4 References 8

CHAPTER 2. IMAGING OF CEREBROSIDES DIRECTLY FROM RAT BRAIN TISSUE BY COLLOIDAL GRAPHITE-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY 12

Abstract 12 Introduction 13 Experimental Section 18 Results and Discussion 21 Conclusions 29 Acknowledgements 30 References 34 Figure Captions 40

CHAPTER 3. DIRECT PROFILING AND IMAGING OF PLANT METABOLITES IN INTACT TISSUES BY USING COLLOIDAL GRAPHITE-ASSISTED LASER DESORPTION IONIZATION MASS SPECTROMETRY 53

Abstract 53 Introduction 54 Experimental Section 57 Results and Discussion 61 Acknowledgement 67 References 70 Figure Captions 75

CHAPTER 4. DIRECT PROFILING AND IMAGING OF EPICUTICULAR WAXES ON ARABIDOPSIS THALIANA BY LASER DESORPTION/IONIZATION MASS SPECTROMETRY USING SILVER COLLOID AS A MATRIX 88

Abstract 88 Introduction 88 Experimental Section 90 Results and Discussion 93 Conclusions 102

iv

Acknowledgement 103 References 109 Figure Captions 111

CHAPTER 5. COLLOIDAL SILVER LASER DESORPTION/IONIZATION MASS SPETROMETRY OF STEROLS AND DIRECT PROBING OF CHOLESTEROL ON ASTROCYTE CELL MONOLAYER 124

Abstract 124 Introduction 125 Experimental Section 127 Results and Discussion 130 Conclusions 133 Ackowledgement 133 References 134 Figure Captions 137

CHAPTER 6. GENERAL CONCLUSIONS 144

APPENDIX 1. SUPPORTING FIGURES FOR CHAPTER 2 146

Figure Captions 146

APPENDIX 2. DIRECT PROFILING AND MS IMAGING OF SMALL METABOLITES FROM FRUITES BY COLLOIDAL GRAPHITE-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY 155

Abstract 155 Introduction 156 Experimental Section 159 Results and Discussion 161 Acknowledgements 167 References 169 Figure Captions 174

APPENDIX 3. SUPPORTING INFORMATION FOR CHAPTER 3 188

Figure Captions 191

ACKNOWLEDGEMENT 194

v

ABSTRACT

Matrix-assisted laser desorption/ionization(MALDI) mass spectrometry(MS) has

been widely used for analysis of biological molecules, especially macromolecules such as

proteins. However, MALDI MS has a problem in small molecule (less than 1 kDa) analysis

because of the signal saturation by organic matrixes in the low mass region. In imaging MS

(IMS), inhomogeneous surface formation due to the co-crystallization process by organic

MALDI matrixes limits the spatial resolution of the mass spectral image. Therefore, to make

laser desorption/ionization (LDI) MS more suitable for mass spectral profiling and imaging

of small molecules directly from raw biological tissues, LDI MS protocols with various

alternative assisting materials were developed and applied to many biological systems of

interest.

Colloidal graphite was used as a matrix for IMS of small molecules for the first time

and methodologies for analyses of small metabolites in rat brain tissues, fruits, and plant

tissues were developed. With rat brain tissues, the signal enhancement for cerebroside

species by colloidal graphite was observed and images of cerebrosides were successfully

generated by IMS. In addition, separation of isobaric lipid ions was performed by imaging

tandem MS. Directly from Arabidopsis flowers, flavonoids were successfully profiled and

heterogeneous distribution of flavonoids in petals was observed for the first time by graphite-

assisted LDI(GALDI) IMS.

Aqueous-based colloidal silver solution was also investigated as an alternative matrix

for IMS application. For Arabidopsis thaliana wild-type and its cer2 mutant flowers, direct

profiling and imaging of cuticular wax compounds by silver LDI MS and gas

chromatography (GC) - MS were carried out for the first time and cuticular wax metabolites

of them were compared for predicting the function of cer2 gene products. Results from silver

LDI MS showed a good agreement with those from traditional GC-MS analysis and we

vi

propose that cer2 gene mutation mainly affects the conversion from C30 fatty acid to C29

alkane in wax biosynthesis pathway. We also applied silver LDI MS to probe cholesterol,

which is the major component of lipid raft domains, from the Astrocyte cell monolayer. With

colloidal silver, cholesterol was readily detected with high sensitivity and cholesterol level

changes on cell monolayer by methyl β-cyclodextrin treatment were successfully assayed by

introducing relative intensity profiling. Results from more rapid, and simpler silver-LDI MS

cholesterol assay method also showed a good agreement with those from traditional

enzymatic fluorometry cholesterol assay method.

1

CHAPTER 1. GENERAL INTRODUCTION

Dissertation Organization

This dissertation begins with a general introduction of small molecule analysis by

laser desorption/ionization (LDI) mass spectrometry (MS) and imaging mass spectrometry

(IMS). The following four chapters are organized with published papers and a manuscript to

be submitted. Chapters two and three are comprehensive studies of LDI MS and IMS of

small metabolites in intact animal and plant tissues by using colloidal graphite as a matrix.

Chapters four and five are projects related to LDI MS and IMS of small metabolites in plant

tissues and cell monolayer by using colloidal silver as a matrix. Tables, cited literature, and

figures for each chapter were placed at the end of each chapter. Chapter six includes

summary of work and the general conclusions. The following three appendixes include the

extended work related to chapter two and supporting information for chapter two and three.

Laser Desorption Ionization Mass Spectrometry

Since the concept of the mass spectrometry was introduced by J.J Thomson’s cathode

ray tube experiment, mass spectrometry has been developed over 100 years by innovative

researchers and has become one of the most important analysis techniques in almost every

field of natural sciences. Mass spectrometry is the analytical technique measuring mass and

charge state of the analyte. In mass spectrometry (MS), the most important step is the

ionization step because this step makes neutral molecules detectable by converting them to

charged ions. Ionization can be done through various mechanisms such as protonation,

deprotonation, cationization, electron ejection, and electron capture. To achieve ionization

through one or more mechanisms above, many ionization techniques have been developed.

Electron ionization (EI) is the classical ionization technique for MS had and has been

used as the primary ionization techniques in the early stage of MS. EI is based on the

2

interaction between emitted electrons and neutral analytes. In 1960 and 1970’s various

ionization methods such as chemical ionization1, electrospray ionization2, field desorption

ionization3, plasma desorption ionization4 and atmospheric pressure chemical ionization5

techniques were developed for MS. In early 1980’s, inductively coupled plasma was

introduced as an ion source for MS6 and fast atom bombardment technique has also

developed for an ion source.7

Laser sources were demonstrated as a fast surface heating source for generating atom

ions from solid samples8 a few years after discovery of lasing in 1960. Since then, laser-

induced desorption/ionization techniques have been thoroughly investigated as ion sources

for MS. In 1978, polar, nonvolatile organic molecules were ionized and detected by using

submicrosecond pulsed laser.9 Those molecules were ionized through cationization and

detected as sodium or potassium adduct ions.9 In the 1980’s, ultra fine metal powder

(UFMP) which had been used for alloy production was introduced as an assisting material for

laser desorption.10 Compared to bulk material, UFMP has much smaller dimensions which

are in the range of the long light wavelength. Therefore, UFMP could absorb energy more

efficiently from the light source without loss or dispersion of heat and high temperature

required for intact molecule desorption could be achieved by using UFMP as an assisting

material.10 With UFMP, intact polyethylene glycols were detected with very little

fragmentations.11 The use of UFMP for LDI MS was further developed by Tanaka. He used a

UFMP suspension in glycerin as an assisting material for LDI MS, and macromolecules over

100 kDa were observed without fragmentation by this method.12 Inspired by UFMP

suspension matrix for LDI MS, Karas and Hillenkamp further optimized this methodology

for macromolecule analysis13, 14. By using nicotinic acid as a matrix, they observed several

proteins including lysozyme, trypsin, and albumin in the form of molecular ion (MH+).13 LDI

MS with organic acids as matrixes is referred to as matrix-assisted laser desorption/ionization

mass spectrometry, MALDI MS. With elctrospray ionization (ESI) technique15, MALDI MS

3

has become the most widely-used soft-ionization technique for macromolecule analysis,

especially proteins.

Laser Desorption Ionization Mass Spectrometry of Small Molecules

Application of MALDI to small molecule analysis (<1000 Da) seems to be

problematic because of a high degree of signal suppression in the low mass region by

dominant matrix ion signals. However, MALDI MS is still attractive in small molecule

analysis because of the direct sampling capability from complex mixtures and the tolerance

for contaminants. With successes in interfacing between MALDI sampling part and a variety

of mass analyzers, the instrumental capability of LDI mass spectrometers such as mass

spectral resolution and tandem MS capability is no longer a limiting factor any more in small

molecule analysis. In addition, great achievements in alternative sample preparation methods

for LDI MS allow us to detect small molecules with less severe matrix interference and/or

sample inhomogeneity.

First, organic matrixes which have relatively large molecular weights and therefore

there was no interference present in the low mass region were used. For example, meso-

tetrakis(pentafluorophenyl) porhyrin (MW. 974.46) was used as a matrix to analyze low

molecular weight alkylphenol ethoxylates which range from m/z 300 to m/z 800.16 Second,

alternative inorganic matrixes such as cobalt powder12, silver colloids17, gold nanoparticles18

and carbon particles were used to analyze small molecules. Among those, carbon particles

including graphite, carbon powder, and carbon nanotubes showed relatively clean

background which is suitable for small molecule analysis. Examples of small molecule

analysis by using carbon materials are reviewed briefly in this dissertation at the introduction

part in Chapter 2. Recently, 30nm-sized silicon nanoparticles were used as a matrix to

analyze various drug, small peptide, and pesticide molecules.19 Interestingly, much lower

laser fluence was required for the silicon nanoparticle matrix compared to conventional

4

MALDI matrixes.19 Third, electrochemically etched porous silicon surfaces without any

additional matrix were used for small molecule analysis by LDI MS. This technique is

referred to as desorption/ionization on silicon MS (DIOS MS).20 Various classes of small

molecules including carbohydrates were analyzed with very low detection limit and with low

background.21-23 Further development on DIOS has been made by utilizing silicon nanowires

as sample support and it required much lesser laser fluence than porous silicon surface or

conventional MALDI environment.24 Lastly, nanostructures coated with liquid-phase

perfluorinated initiator molecules were used as sample support for both LDI MS and SIMS.25

This technique is called as ‘nanostructure initiator MS (NIMS)’. NIMS showed greater

sensitivity (~tens of attomoles) over MALDI and ESI in detecting small molecules including

lipids and drug molecules.25

Imaging Mass Spectrometry of Small Molecules

Pulsed laser-based or energetic particle-based techniques in mass spectrometry have

the capability of generating ions directly from the specific location of sample surfaces. This

capability of spatial sampling allowed us to investigate chemical spatial distribution by

performing serial data collection through sample surfaces. This ‘microscope-concept’

approach by mass spectrometry is called as ‘imaging mass spectrometry (IMS)’ or mass

spectral imaging’. Major methodologies used for IMS are MALDI MS26 and secondary ion

MS (SIMS)27. MALDI IMS was first introduced by Caprioli group.28 MALDI IMS is

advantageous over SIMS in detecting intact large molecules (>1000 Da). However, since the

spatial resolution is limited by laser spot size in MALDI IMS, a spatial resolution of MALDI

(10 to hundreds of microns) is worse than that of SIMS (~100 nm). To get higher spatial

resolution in MALDI IMS, decreasing the laser spot size close to the diffraction limit29 or

using astigmatic optics with a position-sensitive detector30, 31 were demonstrated. In addition,

homogeneous deposition of matrixes is critical in MALDI IMS because all conventional

5

MALDI matrixes crystallize inhomogeneously on sample surfaces. For homogeneous matrix

deposition, finely controlled matrix spraying devices such as acoustic droplet ejection

instrument and piezoelectric microdispenser have been developed.32-34

Because of the soft-ionization characteristic of MALDI, MALDI IMS has been

mainly used for studying protein distribution from tissue sections35-37. However, small

molecules below 1 kDa such as drug molecules38, 39 and endogenous primary or secondary

metabolites were also spatially investigated from many biological systems by MALDI IMS.

Among various primary and secondary metabolites, lipid is the major class of compounds in

small molecule imaging by MALDI IMS because of their abundances in tissue samples.

However, there are two major challenging issues in IMS of small molecules. First, peaks

from conventional MALDI matrixes are dominant in the low mass region and these peaks

interfere with or suppress signals from small sample molecules. To overcome this, matrix-

free methodology such as IR-MALDI was applied to profile plant metabolites40, or matrix-

embedded surfaces such as clathrate nanostructures25 and silicon41 were employed to image

small molecules from intact tissues.

Second, several isobaric ions can be associated in one nominal m/z value which can

cause wrong or overlapped spatial information for a specific compound when generation of

mass spectral images was simply based on extracting intensity values from mass spectra.

Because of compositional similarities of small metabolites, there are many possible overlaps

by several different compounds in the low mass region. To separate distributions of isobaric

ions, imaging tandem MS (IMS/MS)42, high mass resolution MS36, and ion mobility

spectrometry43 were employed.

In IMS/MS, first generation product ions which were specifically from only one of

isobaric ions were chosen for generating chemically selective images. For example, both

sodiated phosphatidylcholine 38:6 ions ([PC 38:6 + Na]+) and DHB matrix cluster ions

contributed the peak intensity at m/z 828.44 But distribution of these two ions were

6

successfully separated by generating images of their specific product ions at m/z 769 (neutral

loss of 59 Da, loss of PC headgroup) and at m/z 652 (loss of a sodiated DHB molecule).44

One major disadvantage of IMS/MS is that it is a time-consuming process because a tissue

sample needs to be scanned separately for all single m/z values which were associated with

several isobaric ions.

High mass spectral resolution and accurate mass measurement by using MALDI

fourier transform ion cyclotron resonance(FTICR) MS can resolve isobaric ions which

cannot be resolved by low-mass resolution TOF or ion-trap mass spectrometers. For example,

Images for three peptides within 0.24 Da range at m/z 1293 were successfully obtained from

the rat brain tissue.36 Mass accuracy was 6 ppm in this experiment.36 However, high mass

resolution imaging is also time-consuming process because of longer measuring time by FT-

ICR.

Ion mobility spectrometry is a real-time gas phase ion separation technique.45, 46

Because ion mobility separation was performed prior to mass analysis, detected ions bear the

information of ions mobility drift time as well as their m/z values. Isobaric ions from

different classes can be separated by choosing different drift time region. For example, lipids

detected from rat brain tissues showed about 12% longer drift time than isobaric peptides.47

Therefore, signals from lipids were separated from chemical noises and other isobaric ion

signals by choosing a specific mobility drift time.43 However, acquiring mass and drift time

are limited in the current software and hardware instrumentation of ion mobility spectrometry

because the allowed data capacity is not enough to process all ions collected from one

scanning point.43, 47

7

(a) H

igh

Mas

s R

esol

utio

n(b

) Ion

Mob

ility

Pro

duct

ion

atm/z

773

(NL

59)

Pro

duct

ion

atm/z

670

(NL

162)

0%10

0%

m/z

832

(c) M

S2Im

agin

g

Figure 1. Isobaric ion separations in IMS. Isobaric ions can be separated by (a) high

mass spectral resolution MS36, (b) ion mobility MS43, (c) tandem MS42.

8

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12

CHAPTER 2. IMAGING OF CEREBROSIDES DIRECTLY FROM RAT

BRAIN TISSUE BY COLLOIDAL GRAPHITE-ASSISTED LASER

DESORPTION/IONIZATION MASS SPECTROMETRY

A paper published in Analytical Chemistry*

Sangwon Cha and Edward S. Yeung

Abstract

Graphite assisted laser desorption/ionization (GALDI) mass spectrometry (MS) was

investigated for analysis of cerebrosides in complex total brain lipids extract. Conventional

MALDI MS and graphite GALDI MS were compared regarding lipid analysis by using high-

vacuum (HV, <10-6 Torr) LDI time-of-flight (TOF) mass spectrometry and intermediate

pressure (IP, 0.17 Torr) linear ion trap (LIT) mass spectrometry. Cerebrosides were not

detected or detected with low sensitivity in MALDI MS because of other dominant

phospholipids. By using GALDI, cerebrosides were detected as intense mass peaks without

prior separation from other lipid species while mass peaks corresponding to

phosphatidylcholines (PCs) were weak. The signal increase for cerebrosides and the signal

decrease for PCs in GALDI MS were more significant in HV than in IP. MSn experiments of

precursor ions corresponding to cerebrosides and PCs in brain lipid extract were performed

for identifying the detected species and for distinguishing isobaric ions. 22 cerebroside

___________________________________________________________________________

* Reprint with permission from Analytical Chemistry 2007, 79(6), 2373-2385.

Copyright © 2007 American Chemical Society

13

species were detected by GALDI whereas 8 cerebroside species were detected by MALDI.

Sulfatides in brain lipid extract were also easily detected by GALDI MS in the negative ion

mode. By forming a colloidal graphite thin film on rat brain tissue, direct lipid profiling by

imaging mass spectrometry (IMS) was performed. Chemically-selective images for

cerebrosides and sulfatides were successfully obtained. Imaging tandem mass spectrometry

(IMS/MS) was performed to generate images of specific product ions from isobaric species.

Introduction

Cerebrosides are one class of glycosphingolipids. A cerebroside is composed of a

hexose (galactose or glucose) and a ceramide consisting of a sphingosine or a sphinganine

base and an amide-linked long chain fatty acid. Depending on the hexose unit, a cerebroside

can be called a galactosylceramide (GalCer) or a glucosylceramide (GlcCer). As mediators,

cerebrosides are involved in many biological processes, such as cell adhesion, cell growth,

cell morphogenesis, and cell-to-cell communication.1-3 Cerebrosides also act as receptors or

as binding sites for viruses on a cellular membrane.4 Deficiency of GalCer causes abnormal

function and local instability during myelination.5 Abnormal accumulation of GalCer or

GlcCer also results in Krabbe disease or Gaucher’s disease, respectively. This increased level

of GalCer or GlcCer is caused by a deficiency of galactosylceramidase or

glucocerebrosidase.6 Krabbe disease causes severe mental degeneration because of

insufficient development of myelin and Gaucher’s disease leads to bone damage, anemia, and

enlargement of spleen and liver.6 In brain tissue, GalCer species are abundant,7, 8 at up to 40

mol% of the phosphatidylcholines (PCs) in rat brain cortex depending on their locations.8-10

Among cortex parts, GalCers are 8 to 10 times more enriched in white matter than in gray

matter.3 In addition to GalCers, 2-hydroxy GalCer species are also abundant in mammalian

brain tissues and their total amount is about 50% of GalCer species.3

14

Since soft ionization techniques for mass spectrometry (MS) such as matrix-assisted

laser desorption/ionization (MALDI) and electrospray ionization (ESI) have been

introduced,11-13 many researchers applied these techniques to analyze lipids. Excellent recent

reviews about lipid analysis by using MALDI or ESI technique can be found elsewhere.10, 14,

15 Lipid analysis with MALDI has the potential advantage over ESI in sample preparation

because of the possibility of using raw biological materials such as tissue sections directly

(without extraction) to obtain spatial information. MALDI MS, however, has a problem with

analyzing lipid mixtures because ionization efficiencies are different according to their head

groups. The presence of PCs and sphingomyelines (SMs) which have a quaternary

ammonium polar head group has been known to suppress signals of other lipid species in the

positive ion mode.16 For lipid analysis with MALDI MS, the most common organic matrix is

2,5-dihydroxy benzoic acid (DHB).17-19 Using DHB with the addition of cesium ion (Cs+)

resulted in reducing spectra complexity and enhancing sensitivity.20, 21 Other matrixes, such

as 2,6-dihydroxyacetophenone (DHA), sinapinic acid (SA), α-cyano-4-hydroxycinnamic

acid (CHCA), p-nitroaniline (PNA), and others, have also been tested,17, 19-21 PNA

generated good profiles of PEs in the presence of PCs and SMs.20 CHCA and SA, however,

suffered from interference signals originated from matrixes. Their low solubility in methanol

was also problematic.14, 17

Whereas numerous MALDI MS analyses of phospholipids have been reported and

many MALDI MS analyses of gangliosides which consists of a glycosphingolipid and one or

more sialic acids have been performed,19, 22-28 relatively little research has been carried out

on the analyses of cerebrosides by using MALDI MS despite their biological importance.

Harvey examined comprehensively the applicability of MALDI MS to sphingolipids and

glycosphingolipids.18 Analysis of less-polar neutral and acidic cerebrosides’ derivatives in

monkey brain was performed by MALDI MS after serial chromatographic separations of

cerebroside-related compounds.29 Yurkova and coworkers induced free-radical

15

fragmentations of cerebrosides by irradiation of γ-ray of cerebroside-containing micelles and

analyzed the lipid extracts from these irradiated micelles by MALDI MS.30 Fujiwaki and

coworkers analyzed sphingolipids in tissues and body fluids from patients with Gaucher’s

disease and found that cerebrosides/SM ratio was elevated in samples from patients with

Gaucher’s disease.23, 31 However, all analyses of cerebrosides mentioned above required one

or more separation steps for isolating glycosphigolipids from other lipid species before MS

analysis.23, 29, 31 Without separation, it is hard to detect cerebrosides by conventional

MALDI MS because phospholipids, especially PCs, are usually dominant in crude extracts

from eukaryotes and the m/z region of phospholipids in the mass spectra substantially

overlaps that of cerebrosides.

Many types of graphite matrices have been suggested as alternative matrices for laser

desorption/ionization (LDI) mass spectrometry because they are near blackbody and disperse

the energy very effectively. Graphite has been used in forms of suspension in glycerol32, 33

or 2-propanol,34 powder35 and plate.36-39 These particles or flakes can range from 2 µm to

150 µm. Sunner and coworkers first showed that graphite matrix in glycerol helped the

detection of proteolytic digest of cytochrome c and cytochrome c itself.32 Further

development of graphite/liquid matrix was achieved by Dale and coworkers and proteins,

oligosaccharides, and synthetic polymers were successfully detected with a glycerol/graphite

matrix.33 The aging of the triterpene in mastic and dammar films was also studied with

graphite powder as a matrix.35 With graphite plate, poly(methylsilsesquioxane)s,38 fatty

acids,39 and synthetic polymers36, 37 were analyzed. Peng and coworkers developed an

interface for thin-layer chromatography (TLC) plate scanning by atmospheric pressure (AP)

LDI MS. They used graphite particle suspension in 2-propanol as a matrix for detecting SMs

and PCs directly from the TLC plate.34 Graphite trapped in silicon polymer was also used for

the surface support to facilitate detecting peptides and proteins with desalting effect.40 Pencil

leads, which are mixed forms of graphite, wax, and clay were used as a matrix to analyze

16

actinide materials and as a calibrant.41 Activated carbon powder was used for detecting

various organic compounds including peptides, prometryn, and hydrochlorothiazide on the

TLC plate.42 Functionalized fullerenes, C60((CH2)2COOH)n or C60(C11H23)n, were also

used for the detection of peptides and phospholipids.43 Recently, carbon nanotubes or

oxidized carbon nanotubes were suggested as matrixes for detecting small peptides, small

oligosaccharides, and cyclodextrins.44, 45 Oxidized carbon nanotubes, which have carboxyl

groups on oxidized surfaces of carbon nanotubes, have more polar surfaces and increased

solubility in aqueous solution.46, 47

For imaging mass spectrometry (IMS), several ionization techniques such as matrix

enhanced secondary ion mass spectrometry (ME-SIMS)48, metal-assisted SIMS,49, 50

MALDI, and cluster SIMS51 have been used. The advantages and disadvantages of these

ionization methods for IMS are well described in the recent review article.52 Briefly, SIMS

has the advantage in spatial resolution but MALDI is more suitable for detecting intact

biological macromolecules. MALDI is also advantageous in terms of instrumental simplicity

and cost. IMS with MALDI has been applied to biomarker studies and many other

pathologically interesting case studies. 53-58

There are two major issues in MALDI IMS. First, spatial resolution is usually limited

by the laser spot size, which usually ranges from 80 µm to 200 µm in diameter. Spengler and

coworkers decreased the spot size to about 0.6 µm by modifying the focusing lens.59

Similarly, Luxembourg and coworkers utilized astigmatic optics and a position-sensitive

detector.60, 61 However, the spatial resolution of 4 µm from this system was determined by

the 2D-position sensitive detector and not by the laser spot size.

Second, organic matrices used in conventional MALDI need co-crystallization that

can lead to surface inhomogeneity. Luxembourg and coworkers showed different spectral

profiles throughout the DHB-spotted surface by ME-SIMS.62 Spraying a matrix solution

electrically or pneumatically, immersing the sample in matrix solution, and dispensing matrix

17

solution by a piezoelectric microdispenser were suggested for generating homogeneous

sample surface with matrixes.63-65 Recently, Aerni and coworkers used acoustic droplet

ejection66 to generate 180-200 µm matrix droplets reproducibly on tissues. The other

solution for generating matrix-sample surface is using ionic matrices. Armstrong and

coworkers introduced new ionic liquids, which are basically combinations of acidic MALDI

matrixes (e.g., DHB, SA, CHCA and etc.) and basic organic solvents such as pyridine, as

MALDI matrixes.67 Ionic liquid matrixes showed advantages of homogeneity, signal

reproducibility, and vacuum-stability.68-70 Lemaire and coworkers improved the

performance of MALDI MS and IMS on rat brain tissue by using solid ionic matrixes such as

CHCA/aniline in the negative-ion mode.71 Recently, imaging tandem mass spectrometry

(IMS/MS) of rat brain tissues by using IP-MALDI LIT mass spectrometer has been

reported.72 By doing MS/MS for site-specifically generated ions, separate chemically-

selective images of product ions were generated for the isobaric ions at m/z 828.6 which

could be composed of sodiated PC 38:6, DHB cluster, and phosphatidylethanolamine 38:4

(PE 38:4).72

Here we demonstrated a simple approach for GALDI MS by using an aerosol spray

which contains 2-propanol-based colloidal graphite. Colloidal GALDI and conventional

MALDI mass spectral analyses were performed for standard lipid mixtures which contain

various compositions of PCs and GlcCers in high-vacuum (HV, 10-6 Torr) and at

intermediate pressure (IP, 0.17 Torr). Softer ionization induced by collisional or vibrational

cooling in IP-MALDI resulted in less fragmentation for labile molecules including

gangliosides.24, 25 By performing imaging MS of sample spots prepared by DHB matrix, we

can derive location-specific mass spectral profiles for PC/GlcCers lipid mixtures as in earlier

studies.62, 73, 74 Total brain lipid extract was chosen as a model of a complex lipid mixture

and was analyzed under four different sampling conditions. In addition, GALDI MSn

experiments were performed to identify the ionized species and to examine isobaric ions. We

18

also investigated the applicability of the colloidal graphite spraying method to direct rat brain

tissue analyses and IMS. Finally, overlapping spatial information originating from PC and

GalCer isobaric ions were separated from each other by performing IMS/MS.

Experimental Section

1,2-Dipalmitoyl-sn-glycero-3-phosphorylcholine (PC 32:0) and standard GlcCers

from bovine buttermilk were purchased from Matreya LLC (Pleasant Gap, PA). Fatty acid

composition of GlcCers from bovine buttermilk provided by the manufacturer is 14:0 (trace),

16:0 (15%), 18:0 (3%), 20:0 (2%), 22:0 (31%), 23:0 (28%), 24:0 (17%), and others (4%).

Long chain bases for these GlcCers are all C18-sphingosine (d18:1) bases. Brain total lipid

extract in chloroform solution (10 mg/ml) was obtained from Avanti Polar Lipids Inc.

(Alabaster, AL). DHB from Bruker Daltonics (Billerica, MA) was used. 2-propanol-based

colloidal graphite aerosol spray (Aerodag® G) was obtained from Acheson Colloids (Port

Huron, MI). All other chemicals were obtained from Fisher Scientific (Fairlawn, NJ).

Rat brain was collected from Spargue-Dawley rats from the College of Veterinary

Medicine at Iowa State University and was frozen in liquid N2 immediately. The frozen rat

brain was cryosectioned into 15 µm thick specimens without embedding in the optimum

cutting temperature (OCT) compound. Without the OCT compound, mass spectral

interference is known to be decreased.63 A cryostat from International Equipment Co.

(Needham Heights, MA) was used for cryosectioning. Sectioned tissues were directly

transferred and mounted onto a stainless-steel plate. The prepared tissue sections were stored

at –20 °C before mass spectrometric analysis.

HV (<10-6 Torr) LDI mass-spectrometric analysis was done with the Biosystems

Voyager-DE PRO time-of-flight (TOF) mass spectrometer (Framingham, MA) equipped

with a N2 laser (337 nm, and maximum 180 µJ/pulse). Mass spectra were collected both in

positive ion mode and negative ion mode with a ±20 kV accelerating potential. Mass

19

calibration was performed with lipid standards. An LTQ linear ion trap mass spectrometer

equipped with vMALDI source (Thermo Electron, Mountain View, CA) was used for IP

(0.17 Torr) LDI mass-spectrometric analysis and imaging MS. A description of the LTQ with

vMALDI source can be found elsewhere.75, 76 The laser source in this mass spectrometer is a

fiber-optic guided N2 laser (337 nm, and maximum 280 µJ/pulse before entering the optical

fiber cable). The measured laser spot size is about 100 µm in diameter on the sample plate

surface.

For lipid standard mixtures, 1 mg/ml of PC 32:0 and 1 mg/ml of total GlcCers stock

solution were prepared in chloroform and in 70% chloroform/ 30% methanol respectively.

Two types of lipid standard mixture batches were prepared. One batch contained a constant

concentration of PC 32:0 (0.5 mg/ml) and various concentrations of GlcCers (from 0.005

mg/ml to 0.5 mg/ml). In the other batch, the concentration of GlcCers was kept constant (0.5

mg/ml), but the concentration of PC 32:0 were from 0.005 mg/ml to 0.5 mg/ml. The total

lipid concentrations in the mixtures thus varied from 0.505 mg/ml to 1 mg/ml. Total brain

lipid extract was diluted with chloroform and the final total lipid concentration was 2 mg/ml.

50 mg/ml DHB solution in 70% methanol and 30% water (containing a 0.1% trifluoroacetic

acid) was prepared as a conventional MALDI matrix.

For conventional MALDI MS, 1 µl of sample solution was applied to the stainless

sample plate followed by 1 µl of DHB matrix solution. For GALDI MS of PC/GlcCer

mixtures and brain lipid extracts, colloidal graphite was sprayed directly onto the stainless-

steel sample plate by using the aerosol spray can (Aerodag® G). The distance between the

nozzle of the spray can and the sample plate was kept at 25 cm. Spraying was performed for

10 to 15 s to form a thin graphite film on the sample plate surface. After spraying, the surface

was dried in air at room temperature for 5 min before the application of sample solutions. For

the standard lipid mixture or total brain lipids extract, 1 µl of sample solution was applied

onto the graphite-coated surface by using a micropipette. For brain tissues, colloidal graphite

20

was diluted four times with 2-propanol and the diluted solution was loaded into a sample

bottle for an airbrush. Double-action airbrush, model “Aztek A470” with a 0.30 mm nozzle

from Testor (Rockford, IL), was used. Spraying with 20 psi air pressure was performed 15.4

cm away from the sample plate. This way, the whole rat brain tissue was covered with

colloidal graphite without moving either the airbrush or the sample plate. Spraying for 30 to

40 s gave the strongest signals from analytes and the lowest graphite background signals.

After spraying, samples were allowed to dry in air for 10 min.

In HV-MALDI MS, mass spectra were recorded from the “big, needle-like crystals”

area at the boundary of the sample spot and from the “small crystals” area at the center of the

sample spot separately. These two mass spectra were then averaged and the averaged mass

spectrum was used for data interpretation. In the case of IP-MALDI MS, rastering over a

sample spot was performed. First, for one sample spot, serial optical images were taken every

1 mm-movement of the sample stage in either x- or y-directions. Each segment of the images

has a size of 140 pixels by 170 pixels. These segments of optical images were reconstructed

as one optical image for one sample spot. Second, a sample spot were rastered with a 100 µm

step size. For each spot, a mass spectrum was recorded for desorbed ions by co-adding over

five laser shots. For each MALDI sample spot, a mass spectrum constructed by averaging

mass spectra from all rastering points was used for data interpretation.

For IMS of rat brain tissue, the number of laser shots for each sample spot was first

determined by collecting mass spectra in a small area (usually 10 rastering points) with

automatic gain control (AGC, which keeps ion amounts in the trap constant by changing the

number of laser shots). Based on the average number of shots per spot with AGC, the number

of laser shots was fixed without AGC (usually 5 to 8 shots per spot) when collecting mass

spectra over the whole tissue. The tissue sample was rastered with 100 µm steps. In the case

of IMS/MS, target precursor ions were first selected based on first generation product ion

spectra for the major peaks in the extracted mass spectra and then first generation product ion

21

spectra of the selected precursor ion were collected with spatial information for all rastering

points over the tissue section (instead of collecting full mass profiles). For a 1.8 cm × 0.8 cm

tissue sample, about 10,000 mass spectra were collected over 1.7 h for IMS and 3.1 h for

IMS/MS, respectively.

Chemically-selective images and extracted mass spectra from specific locations were

generated by using the custom software from Thermo (vMALDI Data Browser). Chemically-

selective images were plotted as maps using either absolute intensity values or normalized

intensity values. The normalized intensity is defined as the fractional peak intensity for the

peak of interest compared to the total ion current (TIC) of each mass spectrum. The mass

window for generating chemically-selective images was 0.8 Da.

Results and Discussion

Colloidal graphite surface for GALDI MS. The electron microscopic image of the

graphite surface generated by colloidal graphite aerosol spray is shown in Figure 1. Graphite

particles in the aerosol spray are about 1 µm-sized with flake shapes (Figure 1) and are finer

than most other types of preparations. The graphite surface generated in this manner has

advantages over other methods of generating graphite surfaces. First, this method is fast and

has minimum preparation steps. Only cleaning of the substrate surface (a stainless steel

sample plate), spraying colloidal graphite, and drying the plate in the air are needed for MS.

It took less than 10 min for the whole preparation. Second, after performing MS, the graphite

surface was easily removed by washing with 2-propanol or acetone. The cleaned plate can be

reused for either GALDI MS or conventional MALDI MS. Third, because of using

conventional stainless steel sample plate as a base, the mechanical stability of the sample

plate, which could be an issue when using a pressurized graphite plate, is very good. Last,

because the colloidal graphite spray contains thermoplastic resin as a binder, formation of

graphite dust is much less problematic than when using a graphite/liquid suspension.

22

MALDI and GALDI MS of mixtures of PC and GlcCers at different sample

chamber pressures. As mentioned before, the presence of PCs and SMs prevents the

detection of other lipid species in MALDI MS. To examine whether this phenomenon occurs

in GALDI MS, standard batch solutions of various compositions of PC 32:0 and GlcCers

were analyzed by MALDI MS and GALDI MS at two different sample chamber pressures.

The mass spectra are shown in Figure 2 and mass peak assignments are listed in Table 1 with

relative abundances. With DHB matrix, protonated PC ions are dominant at both pressures

(Figure 2(a), 2(b), and Table 1). However, with colloidal graphite, the sodiated GlcCer ions

were the most intense at both pressures (Figure 2(c), 2(d), and Table 1). The signal intensity

ratios among different lipid species were different depending on sample chamber pressures.

PC to GlcCer signal intensity ratios were higher in IP than in HV with DHB matrix (Figure

2(a), 2(b), and Table 1). This tendency was even more significant with colloidal graphite

(Figure 2(c), 2(d), and Table 1). In other words, the decrease of PC-related mass peaks or the

increase of GlcCer-related mass peaks was more distinct in HV than in IP.

To examine the ion signals as a function of lipid concentration and composition,

various ratios of PC/GlcCers mixtures were analyzed under the four different conditions.

Relative intensities for the major peak of each lipid species are listed in Table 2, and mass

spectra for these lipid standard mixtures are shown in Supporting Information Figure S-1, S-2,

S-3, and S-4. First, the mass peak corresponding to [PC 32:0 + H]+ was dominant in both

HV- and IP-MALDI mass spectra even when the concentration of PC 32:0 was tenths of that

of total GlcCers (Batch 1). Second, in MALDI, no obvious difference between in IP and in

HV was observed in terms of the relative peak intensities. Third, in contrast to HV- and IP-

MALDI, significant peak intensity for the mass peak corresponding to [GlcCer 22:0 + Na]+

was observed in both HV- and IP-GALDI (Batch 2). Fourth, in GALDI, the peak suppression

of PC 32:0 related ions was less in IP than HV (Batch 1) and the peak enhancement for

[GlcCer 22:0 +Na]+ was higher in HV than IP (Batch 2). In other words, IP-GALDI MS may

23

be more suitable for the simultaneous analysis of various lipid species in complex mixtures,

while HV-GALDI MS may be better for the analysis of cerebrosides in complex lipid

mixtures without separation.

Localization of analytes with DHB matrix. Mass spectral studies for elucidating the

incorporation of analytes into DHB matrix crystals and the heterogeneity of MALDI samples

prepared with DHB matrix have already been reported by many researchers.62, 73, 74 Because

PCs and GlcCers showed very different characteristics in ionization, localization of analytes

was examined by LDI imaging MS. Because the size of conventional laser beams at the

target plate (80-200 µm) is bigger than those of most crystals, resolving one matrix crystal

from another is hard to achieve. However, due to the deposition/drying process, there are two

distinct regions which can be macroscopically recognized from the optical image shown as

the first image in Figure 3(a). One region is located at the boundary of the sample spot and is

mainly composed of “big, needle-like crystals”. The other region is at the center of the

sample spot and “small crystals” are distributed heterogeneously throughout this region. The

subsequent images in Figure 3(a) represent chemically-selective images for the major ions

detected from the PC 32:0/GlcCers mixture. As Luxembourg and coworkers pointed out,62,

73, 74 protonated molecules, [PC 32:0 + H]+, showed the most intense peaks at the boundary

of the sample which consists of big matrix crystals. However, sodiated molecules, such as

[PC 32:0 + Na]+, [GlcCer 22:0 + Na]+, and [GlcCer 23:0 + Na]+ showed much higher peak

intensities at the interior of the MALDI sample spot. This phenomenon also can be seen

clearly from the mass spectra extracted from the two different regions (Figure 3(b) and 3(c)).

This indicates that incorrect mass profiles of lipid mixtures could be generated when spectra

was collected and averaged for a certain region but not for the whole sample spot prepared

with DHB matrix. In contrast to DHB matrix, colloidal graphite does not involve any

crystallization process and are much finer in dimension. Therefore, the surface formed by

24

colloidal graphite provides uniform signals without hot spots, and is well suited for chemical

imaging.

MALDI and GALDI MS and MSn of total brain lipid extract at different sample

chamber pressures. Total brain lipid extract was studied under the various ionization modes

because the components and their structures have been relatively well identified or analyzed

by several mass spectral techniques. Mass spectral profiles of the brain lipid extract in

various ionization environments are shown in Figure 4. First, mass peaks from m/z 730 to m/z

810 are dominant in MALDI, whereas mass peaks from m/z 820 to m/z 880 are the major

peaks in GALDI. This tendency is similar to that in the PC/GlcCer lipid standard mixtures.

Second, for MALDI, no major difference between HV and IP was observed (Figure 4(a)

versus 4(b)). Third, for GALDI, the higher mass peak intensities in the region of m/z 820-880

and the lower mass peak intensities in the region of m/z 730-810 are more pronounced in HV

than in IP (Figure 4(c) versus 4(d)). In other words, lipid species in the region of m/z 820-

880 were detected more selectively in HV than in IP. This trend is also analogous to that in

the mass profiles of PC/GlcCer lipid standard mixtures.

To identify the lipid species detected, MS/MS and MS3 experiments for most of the

major peaks the mass spectra of brain lipid extract (Figure 4(b) and (d)) were performed.

Many structural studies of cerebrosides using tandem mass spectrometry have been reported

with ESI MS,3, 10, 77 but not many with LDI MS so far. For example, GALDI 1st generation

product ion spectrum of m/z 850.66, the most intense peak in Figure 4(d), is shown in Figure

5(a). Neutral loss of 162 Da (NL 162) and NL 180 correspond to the loss of C6H10O5 and the

loss of a galactose unit at the head group position of the sphingosine long chain. NL 18,

which corresponds to the loss of water, was also observed. The predominant mass peak at

m/z 484.50 corresponds to the sodiated C18 sphingosine long chain base and m/z 512 can be

assigned as the sodiated aldehyde form of the C18 sphingosine long chain base (see the

scheme on Figure 5(a)). The mass peak at m/z 850.66 can be assigned as [GalCer

25

d18:1/24:0h + Na]+. GalCer d18:1/24:0h has been known to be the major hydroxylated

cerebroside compound in brain.3, 78 Both NL 162 and NL 180 are highly characteristic

patterns in the first generation product ion spectra for precursor ions of cerebrosides. For all

mass peaks assigned as cerebrosides including both standards (data not shown) and the brain

lipid extract, these two NLs were always observed in their first generation product ion spectra.

In addition, the mass peaks at m/z 484 (C18 sphingosine long chain base) and at m/z 486 (C18

sphinganine long chain base) represent also significant mass fragment ions for cerebrosides

and one of both was observed in most cerebrosides (Table 3). To verify the structure of the

cerebroside further, MS3 experiments was also performed for the m/z 484.50 ion (Figure

5(b)). NL 162 and NL 180 were observed again in the second generation product ion mass

spectrum. In addition to these, the loss of NH3 (NL 17) was also observed. The peaks at m/z

203 and m/z 185 could be identified as the sodiated galactose ion and subsequent loss of

water from it.

Mass peak assignments for cerebrosides and PCs based on the major fragment ions

and NLs are listed in Table 3. Only the major ions which have been verified by first

generation product ion spectra are listed. Fragment ions and neutral loss patterns of

cerebroside species have already been explained with Figure 5. For PCs, the characteristic

mass fragment ion m/z 184 (phosphocholine head group), was observed for some PC

precursor ions. NL 18(-H2O), NL 59

(–N(CH3)3), NL 124(-ethyl phosphate), NL 183(-phosphocholine head group) were observed

for PCs. Similar patterns were observed in earlier studies75, 79-81 and the information was

used for identifying PCs. NL 146, NL 162, NL 205 were also observed for some PC

precursor ions. NL 146 could correspond to NL of ethyl phosphate with sodium (ethyl

phosphate + Na – H) and NL 205 could correspond to NL of phosphocholine head group

with sodium (phosphocholine head group + Na – H). NL 162 from PC precursor ions could

correspond to NL of ethyl phosphate with potassium (ethyl phosphate + K – H). Note that

26

there are two neutral losses which have the same decrease of 162 Da but originated from

different species; NL 162 from GalCer precursor ions and NL 162 from adduct ions

consisting of PC and potassium. The difference between these two neutral losses is that NL

162 from GalCers precursor ions was always observed with NL 180 (-galactose) but NL 162

from PC precursor ions was not. In Table 3, NL 162 from PC precursor ions was annotated

as “NL 162k” to distinguish from NL 162 from GalCer precursor ions. As expected from the

analysis of the standard lipid mixture, GALDI gives more informative mass profiles for

cerebroside species whereas MALDI gives more informative mass profiles for PCs.

In Table 3, note that more than one lipid species can be associated with one m/z.

There are two possible causes for these isobaric ions in mass spectrum. First, several types of

adduct ions can be formed, even if two compounds have quite different monoisotopic masses.

In the case of PC 38:4 and PC 36:1, which are present in the brain, their difference in

calculated exact mass is 21.98 Da. This is the same as the calculated exact mass difference

between H and Na. Therefore, [PC 38:4 + H]+ and [PC 36:1 + Na]+ can be detected

simultaneously at m/z 810. Second, if the monoisotopic masses of two or more compounds

are too close to each other (less than 0.1 Da difference), they overlap and cannot be selected

separately for MS/MS experiments. For example, the monoisotopic masses for GalCer

d18:1/24:1 and PC 38:4 are 809.59 Da and 809.67 Da respectively and both compounds are

known to be present in the brain. They were observed together in both MALDI and GALDI

as listed in Table 3.

However, the ratio of [GalCer d18:1/24:1 + Na]+ and [PC 38:4 + Na]+ in MALDI MS

was different from that in GALDI MS. Figure 6 shows the two first generation product ion

spectra of m/z 832. Similar fragment patterns were observed but the relative abundances are

different in the two modes. The mass peak at m/z 773.25 corresponding to NL 59 from PCs is

dominant in IP-MALDI product ion spectrum (Figure 6(a)) while the mass peak at m/z

670.58 corresponding to NL 162 from cerebrosides is the most intense peak in IP-GALDI

27

product ion spectrum (Figure 6(b)). Comparison between the two mass spectra confirms that

GALDI MS is advantageous when cerebrosides need to be analyzed without separation from

the lipid pools, such as crude lipid extracts or tissue samples. In both mass spectra, mass

peaks corresponding NL 43 and NL 87 were also observed. NL 87 could correspond to the

loss of the C3H5O2N from the phosphatidylserine head group82 and NL 43 could be the

neutral loss of aziridine from phosphatidylethanolamine.83 This means that many other lipids,

such as PE, PS, and PG, can also be incorporated into one m/z for the same reasons.

Detection of sulfatides in negative ion mode by GALDI MS. Sulfatides (STs), one

of the derivatives of GalCers, are 3-sulfate esters of GalCers. STs are enriched in brain

tissues and mediate several biological processes including cell growth, cell adhesion, and

morphogenesis.84 By using MALDI MS, STs were successfully detected from brain tissue,

serum and renal tubule cells in earlier studies.19, 85, 86 Because ST has a sulfate group (SO4–),

they are also easily detected in negative ion mode as shown in Figure 7. The hydroxylated

forms of STs were also observed. Since C24 fatty acids are dominant in the mammalian

nervous system,84 STs and hydroxylated STs which have 24:1 or 24:0 fatty acid composition

were observed as the major species here.

IMS and IMS/MS in rat brain tissues by using GALDI MS. To analyze

constituents directly from tissue samples, ionization assisting materials need to be coated on

top of the tissue. Because extract or other liquid samples were loaded on top of the graphite

layer, the thickness of the graphite layer was not critical in extract analysis. In tissue analysis,

however, too small an amount of colloidal graphite could give weak signals and too large an

amount could generate strong interference signals from the colloidal graphite. To spray more

reproducibly, an airbrush was used with the four-times diluted colloidal graphite solution

instead of an aerosol spray can. We note that too dilute (over ten times) a solution could not

give a firmly-coated surface.

28

A lipid mass profile in the positive ion mode was generated from a rat brain tissue as

shown in Figure 8(b). The lipid profile in negative-ion mode is shown in Supporting

Information Figure S-5. To identify lipid species, MS/MS and MS3 experiments were

performed for major peaks in the lipid profile mass spectrum. For example, the mass peak at

m/z 844.50 in Figure 8(b) could be identified as [PC 38:6 +K]+ and [PE 38:4 + 2K – H]+

based on previous studies72, 83 and first generation product ion mass spectrum (See

Supporting Information Figure S-6). Chemically-selective images for the identified ions are

shown in Figure 9. Note that not only the ions listed in Figure 9 but also other isobaric ions

could contribute to these chemically selective images as discussed previously. From the

images in Figure 9, cerebroside-rich areas and cerebroside-deficient areas can be recognized

clearly and the extracted mass spectra from these two regions are shown in Figure 8(c) and

8(d). The mass region of m/z 800-880, where most of the cerebrosides were found, is

obviously different in Figures 8(c) and 8(d) in terms of mass profiles and relative intensities.

To separate the spatial information of isobaric ions from each other, IMS/MS was

performed. The mass peak at m/z 832.58 was chosen here because both PC and cerebroside

species show this common mass peak from the lipid extract analysis. First product ion

spectra of ions at m/z 832.58 (data are not shown) from the rat brain tissue have the same

fragmentation patterns as those from lipid extracts (Figure 6). Chemically-selective images of

the precursor ion at m/z 832, the product ion at m/z 773, and the product ion at m/z 670 are

shown in Figure 10. The spatial distribution of product ions at m/z 670, which corresponds to

NL 162 from [GalCer d18:1/24:1 + Na]+, is similar to those of other GalCer species shown in

Figure 9. Figure 10 shows that the spatial distribution of the two isobaric ions can be clearly

separated by performing IMS/MS.

29

Conclusions

In this study, a simple and effective method of LDI based on colloidal graphite was

developed and was applied to lipid analyses. Comparison between GALDI and MALDI of

standard lipid mixtures clearly showed the increase in signal from cerebrosides for the former,

making the former more suitable for detection of cerebroside species from lipid pools

without separation. With total brain lipid extract, twenty-two cerebroside species were

detected as major compounds by IP-GALDI MS and confirmed by MSn experiments while

only eight cerebroside species were verified by IP-MALDI MS and MSn experiments. From

Table 3 and Figure 4(c), we can conclude that the major mass peaks in HV-GALDI mass

spectrum correspond to cerebroside species. The peak enhancement for cerebrosides and the

peak suppression for PCs were more significant in HV than in IP. Therefore, HV could be

more suitable for selective detection of cerebrosides and IP could be more appropriate for

profiling various kinds of lipid species in complex lipid mixtures. Negative ion mode of

GALDI also showed comparable performance as MALDI for detecting sulfatides in brain

lipid extracts. For rat brain tissue, mass profiles and chemically-selective images for lipids

were successfully obtained with the modified colloidal graphite spraying technique.

Cerebrosides and sulfatides were well detected in tissue analysis as in extract analysis, and

the increase in intensities of cerebrosides facilitated the generation of images for cerebrosides.

Automated MS/MS experiments over the tissue surface and image processing from these

experiments showed the inherent problem of full mass scan data and the need for MS/MS

imaging. However, performing MS/MS for even one precursor ion over the tissue surface is

already time consuming. Therefore, faster protocols for IMS and further development of

IMS/MS are needed. In this work, the issue about sensitivity increase for fragile

biomolecules in IP LDI MS due to stabilization of labile bonds by collisional cooling was not

discussed. Future studies on the analyses of labile molecules such as gangliosides in HV and

IP by using GALDI MS and MSn would be valuable.

30

Acknowledgements

E.S.Y. thanks the Robert Allen Wright Endowment for Excellence for support. The

Ames Laboratory is operated for the US Department of Energy by Iowa State University

under Contract No. W-7405-Eng-82. This work was supported by the Director of Science,

Office of Basic Energy Sciences, Divisions of Chemical Sciences and Biosciences.

Appendixes

Supplemental GALDI mass spectra for lipid mixture standards with various ratios and

rat brain tissues, and product ion mass spectrum for the m/z 844 are listed in Appendix 1. In

Appendix 2, a complete scientific paper which describes GALDI MS studies of fruit samples

is presented.

Table 1. Mass peak assignments with relative intensities for lipid species in lipid standard mixturesa under different sample chamber pressures

Identification

High-Vacuum Intermediate Pressure

Theoretical m/z (Da)b

Observed m/z (Relative

Intensityc) with DHB

Observed m/z (Relative Intensity)

with Graphite

Observed m/z (Relative Intensity) with DHB

Observed m/z (Relative Intensity)

with Graphite

[GlcCer 16:0+Na]+ d 722.55 722.59 (29.4) 722.50 (78.2) 722.66 (12.3) 722.58 (54.8) [PC 32:0+H]+ e 734.57 734.56 (100.0) — 734.50 (100.0) 734.50 (17.6) [GlcCer 18:0+Na]+ 750.58 750.52 (4.4) 750.53 (13.0) 750.66 (2.6) 750.66 (12.8) [PC 32:0+Na]+ 756.55 756.52 (39.7) 756.57 (6.8) 756.50 (81.2) 756.50 (81.2) [PC 32:0+K]+ 772.53 — — — 772.50 (7.8) [GlcCer 20:0+Na]+ 778.62 778.56 (10.1) 778.59 (30.5) 778.66 (5.0) 778.66 (27.3) [GlcCer 21:0+Na]+ 792.63 792.62 (11.0) 792.60 (38.6) 792.66 (5.6) 792.66 (33.7) [GlcCer 22:0+Na]+ 806.65 806.66 (23.6) 806.63 (100.0) 806.66 (16.5) 806.66 (100.0) [GlcCer 23:0+Na]+ 820.66 820.60 (19.6) 820.65 (67.2) 820.66 (13.2) 820.66 (85.1) [GlcCer 24:0+Na]+ 834.68 834.61 (13.1) 834.66 (41.4) 834.75 (8.2) 834.66 (53.8)

aStandard lipid mixture contains 0.5mg/ml of PC 32:0 and 0.5mg/ml of total GlcCers. bMasses are monoisotopic. cRelative intensity = [(Intensity of relevant mass peak)/(Intensity of the most intense mass peak in the mass spectrum)] × 100. dAll glucosylceramide standards have C18 sphingosine (d18:1) base and the numbers m:n correspond to the number of the total carbons (m):number of double bonds (n) in the amide-linked fatty acid. eNumber x:y corresponds to the number of the total carbons of fatty acids at sn-1 and sn-2 position (x): number of double bonds (y) of PC.

31

Table 2. Relative peak intensities of major peaks in lipid standard mixtures with various PC/GlcCers ratiosa Concentration (mg/ml) Relative Intensity with DHB (%) Relative Intensity with Graphite (%)

PC 32:0 GlcCers [PC32:0+H]+ [GlcCer22:0+Na]+ [PC32:0+Na]+ [GlcCer22:0+Na]+

Pressure HV IP HV IP HV IP HV IP

Batch 1

0.25

0.5

346.6 559.3

100

12.4 57.1

100 0.125 186.8 311.6 10.1 33.2 0.025 115.5 134.1 n.d. 7.6 0.005 83.9 112.8 n.d. 5.1

Batch 2 0.5

0.25

100

9.2 8.3

100

634.5 95.0

0.125 8.4 6.0 410.3 33.0

0.025 2.2 4.5 30.5 15.7

0.005 n.d. 3.4 n.d. 8.3

aMass spectra used for calculation are listed in Supporting Information Figure S-1, S-2, S-3, and S-4. bn.d. represents “not detected”.

32

33

Table 3. Mass peak assignments for cerebrosides and phosphatidylcholines in brain lipid extract based on MS/MS experiments

IP-GALDI IP-MALDI Observed Product Ionsa

and Neutral Losses (NLs)b Ions Assigned m/z Ions Assigned Observed Product Ions

and Neutral Losses (NLs) Cerebrosides Cerebrosides

NL 18, NL 162, NL 180 [GalCer d18:1/18:0c

+ Na]+

750

m/z 484, NL 18, NL 162, NL 180 [GalCer d18:1/18:0h

d+

Na]+

766

NL 18, NL 162, NL 180 [GalCer d18:1/22:1 + Na]+

804


806 [GalCer d18:1/22:0 + Na]+

NL 18, NL 162, NL180

m/z 484, NL 18, NL 162, NL 180 [GalCer d18:0/22:0 + Na]+

808 [GalCer d18:0/22:0 + Na]+

m/z 484, NL 18, NL 162, NL180

m/z 484, m/z 512, NL 18, NL 162, NL 180 [GalCer d18:1/23:0 + Na]+

820

m/z 484, m/z 512, NL 18, NL 162, NL 180 [GalCer d18:1/22:0h + Na]+

822 [GalCer d18:1/22:0h + Na]+

m/z 484, m/z 512, NL 18, NL 162, NL180


824


832 [GalCer d18:1/24:1 + Na]+

NL 18, NL 162, NL180

m/z 484, m/z 512, NL 18, NL 162, NL 180 [GalCer d18:1/24:0 + Na]+

834


836 [GalCer d18:1/23:0h + Na]+

m/z 484, NL 18, NL 162, NL180

m/z 486, NL 18, NL 162, NL 180 [GalCer d18:0/23:0h + Na]+

838

m/z 484, m/z 512, NL 18, NL 162, NL 180 [GalCer d18:1/24:1h + Na]

+

[GalCer d18:1/25:0 + Na]+

848

[GalCer d18:1/24:1h + Na]+

[GalCer d18:1/25:0 + Na]+

m/z 484, m/z 512, NL 18, NL 162, NL180


850 [GalCer d18:1/24:0h+Na]+

m/z 484, m/z 512, NL 18, NL 162, NL180


852 [GalCer d18:0/24:0h+Na]+

m/z 486, NL 18, NL 162, NL180

m/z 484, NL 18, NL 162, NL 180 [GalCer d18:1/26:1 + Na]+

860


862


864

m/z 486, NL 18, NL 162, NL 180 [GalCer d18:0/25:0h + Na]+

866


876


878


880 Phosphatidylcholines Phosphatidylcholines

NL 124, NL 146 [PC 34:1 - N(CH3)3 + Na]+

723

734 [PC 32:0 + H]+

m/z 184, NL 59, NL124

NL 124, NL 162k [PC 34:1 - N(CH3)3 + K]+

739

NL 124, NL 146 [PC 36:1 - N(CH3)3 + Na]+

751

NL 59, NL 124, NL146 [PC 32:0 + Na]+

756 [PC 32:0 + Na]+

NL 59, NL 183, NL 205

760 [PC 34:1 + H]+

m/z 184, NL 59, NL 124, NL183

762 [PC 34:0 + H]+

m/z 184, NL 59

NL 59 [PC 32:0 + K]+

772 [PC 32:0 + K]+

NL 59, NL183

NL 59 [PC 34:1 + Na]+

782 [PC 34:1 + Na]+

NL 59, NL 124, NL 183, NL 205

784 [PC 34:0 + Na]+

NL 59, NL 183, NL 205

786 [PC 36:2 + H]+

NL 59, NL 183

788 [PC 36:1 + H]+

NL 59, NL183

NL 59, NL162k [PC 34:1 + K]+

798 [PC34:1 + K]+

NL 59, NL 183

806 [PC 38:6 + H]+

NL 59, NL 124, NL 183

NL 59 [PC 36:2 + Na]+

808 [PC 36:2 + Na]+

NL 59, NL 124, NL 183

NL 59 [PC 36:1 + Na]+

810 [PC 36:1 + Na]

+

a/o [PC 38:4 + H]+

NL 59, NL 124

NL 59 [PC 38:4 + Na]+

832 [PC 38:4 + Na]+

NL 59, NL 124, NL 183

836 [PC 38:2 + Na]+

NL 59, NL 183 a,bSee text for assignments of product ions and neutral losses cGalCer A/B corresponds to galactosylceramide sphingoid long chain base (A)/amide-linked fatty acid (B). dh corresponds to the hydroxyl group at the C2 position of the amide-linked fatty acid.

34

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40

Figure Captions

Figure 1. Scanning electron microscopy image of the colloidal graphite sprayed surface.

Figure 2. LDI mass spectra of the standard lipid mixture under four different conditions,

(a) high-vacuum (HV)-MALDI, (b) intermediate pressure (IP)-MALDI, (c)

HV-GALDI, and (d) IP-GALDI. The standard lipid mixture contains

0.5mg/ml PC 32:0 and 0.5 mg/ml total GlcCers. Mass peak assignments and

relative abundances are listed in Table 1.

Figure 3. (a) On the left is the optical image of the MALDI sample spot consisting of 1

µl of the standard lipid mixture (0.25 mg/ml of PC 32:0 and 0.5 mg/ml of total

GlcCers) and 1 µl of 50 mg/ml of DHB matrix solution. The sample spot size

is about 2.7 mm by 2.4 mm. Following are four chemically-selective images

corresponding to the normalized intensity map (mass peak intensity divided

by total ion current of each point) of the major lipid species. (b) IP-MALDI

spectrum extracted from the region of “big, needle-like crystals” at the

peripheral of the sample spot. (c) IP-MALDI spectrum extracted from the

region of “small crystals” at the interior of the sample spot.

Figure 4. LDI mass spectra of total brain lipid extract under different conditions,

(a) HV-MALDI, (b) IP-MALDI, (c) HV-GALDI, and (d) IP-GALDI in

positive ion mode. Mass peak assignments and corresponding MS/MS data

are listed in Table 3.

41

Figure 5. (A) First generation product ion spectrum of ions detected at m/z 850.66 from

IP-GALDI mass spectrum of total brain lipid extract (Figure 4(d)). The neutral

loss of 18 Da (NL 18) corresponds to the loss of water. NL 162 corresponds to

the loss of C6H10O2 from the sphingosine long chain. NL 180 is the loss of a

galactose unit. Mass peaks at m/z 484 and at m/z 512 correspond to the

sodiated C18 sphingosine long chain and its aldehyde form as seen in the

scheme. (b) First generation product ion spectrum of ions at m/z 484.50 which

are the first generation product ions of m/z 850.66. NL 17 corresponds to the

loss of NH3. NL 162 and NL 180 are the same as those in Figure 5(a). The

precursor ion at m/z 850.66 can be assigned as [GalCer d18:1/24:0h+Na]+.

Figure 6. First generation product ion spectra of ions at m/z 832 from (a) IP-MALDI

(Figure 4(c)) and (b) IP-GALDI (Figure 4(d)) mass spectra of the total brain

lipid extract. NLs of 18, 162, and 180 are the same as those in Figure 5. NL 59,

NL 124, and NL183 correspond to losses of trimethylamine (N(CH3)3), ethyl

phosphate from PC, and phosphocholine head group, respectively. NL 87

could correspond to the loss of the C3H5O2N from the phosphatidylserine

group. Note that NL 59 from PC is dominant in the MALDI mass spectrum

whereas NL 162 and NL 180 from cerebrosides are dominant in the GALDI

mass spectrum.

Figure 7. IP-GALDI mass spectrum of total brain lipid extract in the negative ion mode.

Sulfatides (STs) were mainly detected. ST m:n(h) represents sulfatide with

number of the total carbons (m):number of double bonds (n) in the amide-

linked fatty acid (hydroxylated).

42

Figure 8. (a) Chemically-selective image of ions at m/z 810 with grayscale gradation-

coded intensities. (b) The mass spectrum is the average of mass spectra at all

rastering points on the tissue (10,732 points) in the positive-ion mode. Each

mass spectrum in (c) and (d) was extracted from the small specific area (3 × 3

rastering points) as indicated in (a).

Figure 9. Chemically-selective images in the positive-ion and negative-ion modes.

Major ionic species identified by MS/MS and MS3 experiment were listed

together with the intensity ranges that correspond to the scale bar at the top

center of the figure.

Figure 10. Chemically-selective images of rat brain tissue for (a) the precursor ion at m/z

832, (b) the product ion at m/z 773 which represents NL 59 from PCs, and (c)

the product ion at 670 which represents NL 162 from cerebrosides. Therefore,

the isobaric ions at m/z 832 corresponding to [GalCer d18:1/24:1 + Na]+ and

[PC 38:4 + Na]+ in (a) can be separated into the image for [PC 38:4 + Na]+ in

(b) and the image for [GalCer d18:1/24:1 + Na]+ in (c) by performing

IMS/MS.

43

Figure 1.

44

680 700 720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

680 700 720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

(a)

[Glc

Cer

16:

0 +

Na]

+

[PC 32:0 + H]+

[PC

32:

0 +

Na]

+

[Glc

Cer

20:

0 +

Na]

+

[Glc

Cer

21:

0 +

Na]

+

[Glc

Cer

22:

0 +

Na]

+

[Glc

Cer

23:

0 +

Na]

+

[Glc

Cer

24:

0 +

Na]

+

HV-MALDI(b)

[Glc

Cer

16:

0 +

Na]

+

[PC 32:0 + H]+

[PC 32:0 + Na]+

[Glc

Cer

20:

0 +

Na]

+

[Glc

Cer

21:

0 +

Na]

+

[Glc

Cer

22:

0 +

Na]

+

[Glc

Cer

23:

0 +

Na]

+

[Glc

Cer

24:

0 +

Na]

+

IP-MALDI

6800

10

20

30

40

50

60

70

80

90

100

700 720 740 760 780 800 820 840 860 880 900

Rel

ativ

e A

bund

ance

(%)

m/z

(c)

680 700 720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

(d)

[Glc

Cer

16:

0 +

Na]

+

[PC

32:

0 +

H]+

[PC 32:0 + Na]+

[Glc

Cer

20:

0 +

Na]

+

[Glc

Cer

21:

0 +

Na]

+

[GlcCer 22:0 + Na]+

[GlcCer 23:0 + Na]+

[GlcCer 24:0 + Na]+

[GlcCer 16:0 + Na]+

[PC

32:

0 +

Na]

+

[Glc

Cer

20:

0 +

Na]

+

[Glc

Cer

21:

0 +

Na]

+

[GlcCer 22:0 + Na]+

[Glc

Cer

23:

0+N

a]+

[Glc

Cer

24:

0 +

Na]

+

[Glc

Cer

18:

0 +

Na]

+

HV-GALDI

[PC

32:

0 - N

(CH 3

) 3+

Na]

+

[PC

32:

0 - N

(CH 3

) 3+

K]+

[Glc

Cer

18:

0 +

Na]

+

[PC

32:

0 +

K]+

IP-GALDI

Figure 2.

45

680 700 720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

(b)

680 700 720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

(c)

0.00 0.05 0.10

(a)

[PC 32:0 + H]+

[PC 32:0 + Na]+

[PC 32:0 + H]+

[PC 32:0 + Na]+

[GlcCer 22:0 + Na]+

[PC 32:0 + H]+ [GlcCer 22:0 + Na]+[PC 32:0 + Na]+ [GlcCer 23:0 + Na]+

Figure 3.

46

720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

731.

6273

2.60

734.57

760.57

788.

62

782.57

794.

6379

8.52 80

6.58

810.

59

820.

66 822.

66 834.

68

850.

72720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

720 740 760 780 800 820 840 860 880 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

731.

50

734.50

750.58

756.

50

760.50

768.50

782.50

788.

50

798.

5080

6.50

810.50

832.

58

848.

6685

0.75

766.

5376

8.55

806.

48

822.65

832.

6583

6.66

838.63

850.65

723.

58

751.

4175

3.58 76

3.41

769.

50 772.

50

779.50

788.

6679

0.58

798.

5880

4.50 81

0.58

820.

66

822.58

834.

66

850.66

864.

5886

6.58

(a) (b)

(c) (d)

HV-MALDI IP-MALDI

HV-GALDI IP-GALDI

756.

56

824.

6883

2.73

848.

64753.

57

753.

50

808.

50

822.

66

835.

58

874.

83

804.

48

828.

47

739.

46

749.

36

778.

4478

2.55 79

0.51

794.

60

848.

6685

2.67

866.6586

4.65

868.

67 782.

50

826.

50

836.

6683

2.50

848.

6685

2.58

876.

75

Figure 4.

47

300 400 500 600 700 800 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e Ab

unda

nce

(%)

484.50

512.42 670.58

688.50

763.33

832.58

(a)

300 400 500 600 700 800 9000

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e Ab

unda

nce

(%)

(b)

203.83

322.67

467.42

Amide-linked fatty acid

NL 162

NL 180

NL18

185.92 304.75

484.50NL180

NL162

NL17

OOH

HOOH

O

OH

(CH2)12CH3NH

O(CH2)21CH3

OH

OH

Na+

m/z 484NL 162NL 180

Na+

m/z 512

OOH

HOOH

O

OH

(CH2)12CH3

NH2

OHNL 162NL 180

NL 17

Figure 5.

48

450 500 550 600 650 700 750 800 8500

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

652.

42 (N

L180

)

670.

67 (N

L 16

2)

773.25 (NL 59)

814.

50 (N

L 18

)83

2.58

649.

33 (N

L183

)

708.

42 (N

L 12

4)

745.

33 (N

L 87

)

788.

92 (N

L 43

)

(a)

IP-MALDI

450 500 550 600 650 700 750 800 8500

10

20

30

40

50

60

70

80

90

100

m/z

652.

50 (N

L 18

0)

670.58 (NL 162)

814.

50 (N

L 18

)

Rel

ativ

e A

bund

ance

(%)

832.

50

789.

17 (N

L 43

)77

3.25

(NL

59)

(b)IP-GALDI

Figure 6.

49

780 800 820 840 860 880 900 920 9400

10

20

30

40

50

60

70

80

90

100

m/z

Rel

ativ

e A

bund

ance

(%)

[ST

18:0

- H

]- (80

6.50

)

[ST

18:0

h - H

]- (82

2.41

)

[ST

24:1

- H

]- (88

8.58

)

[ST

23:0

- H

]- (87

8.58

)

[ST

22:0

h - H

]- (86

2.58

)

[ST

20:0

h - H

]- (85

0.50

)

[ST

20:0

- H

]- (83

4.50

)

[ST

26:0

- H

]- (91

8.58

)[S

T 26

:1 -

H]- (

916.

58)

[ST

24:0

h - H

]- (90

6.50

)[S

T 24

:1h

- H]- (

904.

58)

[ST

24:0

- H

]-

(8

90.5

8)

[ST

260h

- H

]- (93

4.58

)[S

T 26

:1h

- H]- (

932.

50)

Figure 7.

50

720

740

760

780

800

820

840

860

880

900

0102030405060708090100

m/z

Relative Abundance (%)

751.

50

756.42

772.42782.

50

798.

50

822.58826.50

850.58

848.

66

868.

41

720

740

760

780

800

820

840

860

880

900

0102030405060708090100

m/z


756.

58

772.

50782.

50

798.

49

810.50

826.50

844.50 848.50852.50

868.50

(c)

(d)

(a)

720

740

760

780

800

820

840

860

880

900

0102030405060708090100

m/z


723.42

756.

50

772.

50782.

58

798.

50

806.50

828.50

844.50

868.

50

852.50848.58

810.10

(b)

810.50

832.58

Figure 8.

51

m/z

888

[ST

24:1

- H

]-

(0-1

2000

0)

m/z

890

[ST

24:0

- H

]-

(0-7

0000

)

m/z

885

[PI 3

8:4

- H]-

(0-1

7500

)

m/z

782

[PC

34:

1 +

Na]

+

(0-2

0000

0)

m/z

810

[PC

36:

1 +

Na]

+

(0-1

3000

0)

m/z

756

[PC

32:

0 +

Na]

+

(0-1

4000

0)

m/z

822

[Gal

Cer

d18

:1/2

2:0h

+ N

a]+

(0-1

3000

0)

m/z

850

[Gal

Cer

d18

:1/2

4:0h

+ N

a]+

(0-1

4000

0)

Opt

ical

Imag

e

Neg

ativ

e Io

n M

ode

Pos

itive

Ion

Mod

e

0%10

0%

Figure 9.

52

Product ion at m/z 773 (NL 59)

Product ion at m/z 670 (NL 162)

0% 100%

m/z 832

Figure 10.

53

CHAPTER 3. DIRECT PROFILING AND IMAGING OF PLANT

METABOLITES IN INTACT TISSUES BY USING COLLOIDAL

GRAPHITE-ASSISTED LASER DESORPTION IONIZATION MASS

SPECTROMETRY

A paper accepted for publication in The Plant Journal*

Sangwon Cha, Hui Zhang, Hilal I. Ilarslan, Eve Syrkin Wurtele, Libuse Brachova,

Basil J. Nikolau and Edward S. Yeung

Abstract

Laser desorption/ionization (LDI)-based imaging mass spectrometry (MS) has been

applied to several biological systems to obtain information about both the identities of the

major chemical species and their localization. Colloidal graphite-assisted LDI (GALDI) MS

imaging was introduced for imaging of small molecules such as phospholipids, cerebrosides,

oligosaccharides, flavonoids, and other secondary metabolites with high spatial homogeneity

due to the finely dispersed particles. Mass profiles and images of Arabidopsis thaliana were

recorded directly from various plant surfaces and cross-sections. The main targeted

metabolites were flavonoids and cuticular waxes, both of which are important in many

aspects of functional genomics, proteomics, and metabolomics. Mass spectral profiles

revealed tissue-specific accumulation of flavonoids in flowers and petals. In addition, many

other location-specific ions were observed. The location and the degree of light-induced

flavonoid accumulation in stem sections were successfully probed by GALDI MS.

___________________________________________________________________________

* Reprint with permission from The Plant Journal 2008,

doi: 10.1111/j.1365-313X.2008.03507.x, Copyright © 2008 Blackwell Publishing Ltd.

54

Introduction

Because low molecular weight metabolites exhibit a variety of different chemical

properties, many analytical methods have been used to assay their structures, abundances,

and locations 1, 2. Among these methods are nuclear magnetic resonance (NMR) spectroscopy 3, 4 for structural analysis of the metabolites, vibrational spectroscopy for metabolic

fingerprinting, and mass spectrometry (MS) for metabolite profiling 5. Gas chromatography-

MS (GC-MS) has been extensively used over the last 20 years 1, 6, 7 because it is a relatively

well-constructed methodology that has good reproducibility and wide applicability to various

classes of metabolites. Moreover, GC-MS has the ability to identify and quantify metabolites.

Since the development of electrospray ionization (ESI) techniques 8 and advances in tandem

MS technologies, liquid chromatography-MS (LC-MS ) is also becoming a workhorse with

high throughput and high sensitivity 9.

It is known that metabolic processes in plants are spatially non-uniform. This is

readily apparent via microscopic examination of plant organs that reveals considerable

heterogeneity in cell morphology and the distribution of pigments (e.g., chlorophylls,

anthocyanins) among these cells. At the biochemical level a very good example of this cell-

level asymmetry is that of C-4 photosynthesis, which requires a distinct distribution of

metabolic processes among mesophyll and the bundle-sheath cells, respectively, to

concentrate carbon dioxide at the active site of RuBISCO (ribulose–1,5-biphosphate

carboxylase/oxygenase). This discovery required the physical separation of the two cell types

before their proteome and/or metabolome could be interrogated. Thus, the development of

analytical techniques that can interrogate metabolites in intact tissue and with high-spatial

resolution would offer the ability to decipher metabolic processes at the cellular level.

Laser desorption/ionization (LDI) MS and matrix-assisted laser ionization/desorption

(MALDI) MS have not been widely used in plant metabolomics mainly because of

difficulties in generating ions from the relatively hydrophobic species in plant tissue.

55

However, the applicability of LDI MS to imaging plant metabolites, including direct

profiling of cuticular wax compounds 10, analysis of phosphatidylcholine 11, condensed

tannins in bark 12, and profiling of plant carotenoids 13 has been successfully demonstrated.

The advantage of LDI MS, over hyphenated techniques (GC-, LC-, and CE- MS) is the

ability to sample biochemicals directly without any extraction protocol. Therefore, the spatial

distribution of the biochemicals is retained.

In laser desorption, the sampling resolution is governed primarily by the laser spot

size. Consequently, the spatial resolution of imaging MS by LDI can be much smaller than

that achievable by traditional methods such as dissecting plant materials followed by

chemical extraction prior to MS -The effort to achieve smaller sampling size by laser

microdissection with traditional GC-MS methods has been reported recently 14. Location-

specific sampling has made it possible for LDI to be employed as a microscope, that is, for

“imaging MS” 15. Imaging MS collects mass spectra consecutively over the sample surface

and reconstructs mass spectral data as an image for each specific compound. In addition to

LDI, ion beam-induced ionization methods such as secondary ionization (SIMS) 16-21 and

beam-induced desorption electrospray ionization (DESI) 22, 23 have also been successfully

applied to imaging MS.

In addition to laser spot size, factors that limit the spatial resolution of LDI imaging

MS include sensitivity of the mass spectrometer, abundance of a metabolite, and

homogeneity of the material added to facilitate ionization. Matrixes in MALDI MS, which

require co-crystallization with sample components to be effective, can decrease the spatial

resolution because of their irregular crystallization patterns. To overcome this, researchers

have introduced alternative matrixes that can be homogeneously distributed on the sample

surfaces. Recently, we used colloidal graphite , a sub-micron flake-like material, as an

assisting material (GALDI MS) for imaging lipids from rat brain slices and also for imaging

secondary metabolites such as flavonoids and organic acids from fruits 24, 25. The other

56

advantages of GALDI MS are that graphite is more hydrophobic, making it compatible with

plant materials, and is a near-blackbody, making it suitable for irradiation with any

wavelength of light. Hence, GALDI MS makes possible to interrogate some classes of

compounds that are not detected by conventional MALDI. Recently, Siuzdak’s group

introduced nanostructure-initiator mass spectrometry (NIMS) where ‘initiator’ molecules

trapped in nanostructures help to ionize intact molecules on their surfaces 26. NIMS can

achieve high spatial resolution because of its structure and it can accept both photon and ion

irradiation.

SIMS has been used for imaging studies of metal ions on plant surfaces 27-32. Recently,

localization of phenolic compounds from wood stems has been examined by time-of-flight

(TOF) SIMS 33, 34. However, most studies by LDI MS imaging have been done on animal

tissue sections such as rat brain slices. Recently, MS imaging of amino acids, sugars, and

phosphorylated metabolites on wheat seeds by using conventional MALDI matrix was

reported 35. IR laser, instead of conventional UV laser, has been used to image several

abundant metabolites from fruits 36. There, the ultimate spatial resolution that can be

achieved is compromised because of the wavelength of light.

Elongation of aliphatic fatty acids to form very long chain fatty acids (VLCFAs) is

the first step in the biosynthesis of components of the cuticular wax layer. This layer makes

plants resistant to external stresses such as insects, pathogens, and water 37-41. Flavonoids

serve as epidermal shields to protect against UV light. In the case of Arabidopsis thaliana,

the major building blocks of flavonoid are flavonols and flavonol glycosides as shown in

Figure 1 42-44. Another major class of flavonoids is anthocyanins and proanthocyanidins, end

product of flavonoid’s biosynthetic pathways 45-47.

Because Arabidopsis is an important model system for plants, and as such the most

highly understood, it is important to be able to analyze its metabolome in situ. The

Arabidopsis plant is small and fragile; therefore its analysis is challenging for sample

57

handling and MS imaging. For the present imaging MS study, we focused on very long chain

fatty acids (VLCFAs) and the flavonoids because we have already demonstrated the ability

of GALDI MS to detect members of these classes of compounds 25 and because of the

breadth of information on the effects of genetic mutants and environmental perturbations on

these metabolites. In addition, we discuss methodological details about MS imaging of

surfaces in small-size plants in terms of sample preparation, methods for imaging, and other

experimental concerns. Finally, as a model system, we describe spatial probing of flavonoid

accumulation from light-treated stem sections.


Chemicals. Standards such as long-chain fatty acids, flavonoids, and histochemical

staining reagents, diphenylboric acid 2-amino-ethyl ester (DPBA) and p-

dimethylaminocinnamaldehyde (DMACA), were purchased from Sigma-Aldrich (St. Louis,

MO). 2-Propanol-based colloidal graphite aerosol spray (Aerodag G) was obtained from

Acheson Colloids (Port Huron, MI).

Plant growth conditions. Seeds of Arabidopsis thaliana Columbia-0 ecotype (Col-0)

were surface sterilized for 1 min in 300 µl 50% ethanol, 10 min in 300 µl 50% bleach

containing 1% Tween 20, and washed with 3 changes of 300 µl sterile water. Seeds were

sown on MS media in Petri plates, and kept at 4 ˚C for 4 days. The plates were then moved to

a growth room and seedlings were transferred to pots containing soil (LC1 Sunshine Mix)

under continuous illumination (100 µmol m–2 s–1) at 23 ˚C.

Light treatment. Plants were grown in a growth room for 40 days under continuous

illumination (100 µmol m–2 s–1) at 23 ˚C in pots containing soil (LC1 Sunshine Mix). At the

time of the experiment, half of the plants (control) were left in this growth room, and the

other half were transferred into a second growth room and grown in continuous illumination

under high light intensity (750-800 µmol m–2 s–1) at 23 ˚C. Fourteen days after transfer, stem

58

samples were harvested, frozen in liquid nitrogen, and 50-80 μm thick sections were cut on a

cryostat (International Equipment Co., Needham Heights, MA).

Flavonoid staining. Cryosectioned stem samples were stained for 15-20 min with

saturated 0.25% (wt:vol) DPBA 48 with 0.02% (vol:vol) Triton X-100 and viewed with an

epifluorescent microscope (Zeiss AxioPlan II compound fluorescent microscope using an

AxioCam MRM camera (for MRC color) and AxioVision software, Carl Zeiss Inc.,

Thornwood, NY) with a FITC filter (excitation, 450-490 nm; suppression, long pass/515 nm)

according to Murphy et al. (2000) and Lazar and Goodman (2006); flavonols (kaempferol

and quercetin) stain orange, naringenin stains yellow and chlorophyll autofluorescence is red.

DMACA staining reagent (0.1% DMACA in 6N HCl:95% ethanol, 1:1) 49 was used

to detect flavonols (soluble phenols, soluble flavanols and proanthocyanidins) 50. After

staining with this reagent for 5-10 min, cryosectioned stem samples were washed three times

with distilled water and observed under the light microscope; flavonols stain blue and purple-

brown colors.

Plant sample preparation for mass spectral profiling and imaging. For leaves or

flowers, samples were attached to a stainless steel target plate of similar dimensions as a

microscopic glass slide using conductive double-sided tape (3M, St. Paul, MN). Any area

inadvertently damaged by forceps was excluded when collecting mass profiles. To attach

samples firmly onto the target plate, air pressure from a nitrogen gas cylinder was used. After

attachment, samples on the target plate were dried for 30 min under moderate vacuum (~50

Torr). In some experiments, the bottom or top halves of fresh Arabidopsis leaves were dipped

in chloroform for 30 s or 1 min to remove wax layers.

For stem sections, relocation of compounds due to water condensation is a

challenging issue because frozen sections must be thaw-mounted directly onto the stainless

steel target plate. To minimize condensation, stem sections on target slides were dried in a

semi-sealed box half-filled with desiccant by purging with a flow of dry nitrogen.

59

Colloidal graphite solution diluted 4X with 2-propanol was used for spraying

colloidal graphite onto samples. The spraying device was an airbrush, model Aztek A470

with a 0.30 mm nozzle from Testor (Rockford, IL). Spraying was at 20 psi, 8 cm from the

sample plate. Optimized spraying times as determined by mass spectral qualities were 30-40

s for leaves and 20-25 s for flowers and stem sections. Colloidal graphite dried in less than 10

s.

Sample preparation including drying process is a challenging task. We have tried

using fresh samples (without drying) for whole organ samples (leaves and whole flowers).

By comparing MS profiles from the fresh sample with those from the dried sample, we did

not observed any significant difference between them for our targeted metabolites. However,

for fresh samples, they shrunk during data collection under the sample chamber pressure

(0.17 Torr) even if they were firmly attached, and the chemical images and optical images do

not match very well. Therefore, pre-drying under the moderate vacuum pressure (~50 Torr)

was needed to prevent this. For stem cryosections, special care was needed to prevent

condensation-induced chemical relocation. Other experiments show that without such dry N2

control, water droplets formed and flavonoids were seen smeared all over the cross section.

Mass spectrometry. Mass spectra were collected with a Thermo Finnigan LTQ

linear ion trap mass spectrometer equipped with vMALDI source (Mountain View, CA). In

this mass spectrometer, nitrogen laser emission (337 nm, maximum energy of 280 µJ/pulse,

and maximum frequency of 20 Hz) was guided through a 200-µm fiber optic cable. After

passing through several optical components, 100 µm diameter laser spots were obtained at

the sample plate surface. In contrast to high vacuum sampling environments (~10-6 Torr) of

conventional MALDI TOF instruments, the LTQ mass spectrometer has the intermediate-

pressure (0.17 Torr) sampling environment which can lead to softer ionization by vibrational

and collisional cooling effects. All mass spectra were collected in the negative-ion mode and

the scanning m/z range was set from m/z 150 to m/z 1000. For unknown peaks acquired

60

directly from plant samples, peak identification were carried out by matching monoisotopic

masses of metabolites listed in databases—TAIR (http://www.arabidopsis.org/) and internal

GC-MS database—with observed mass values. Identities were confirmed by comparing

product ion spectra (up to the third generation) from unknown peaks with those from

standards or from literature data.

Mass spectral imaging and image processing of leaves. For untreated leaves, the

number of laser shots required was estimated by collecting mass spectra in a small area

(usually 5 to 10 rastering points) by turning on automatic gain control (AGC, which keeps

the ion amounts in the trap at a similar range by varying the number of laser shots) feature of

the mass spectrometer. The optimum number of laser shots was determined and fixed based

on the average number of laser shots when collecting mass spectra over the whole sample.

For chloroform-dipped leaves, however, mass spectra were collected with AGC because they

have several different surface characteristics in one sample which can lead to variations in

ion yield. The sample was scanned with a step size which ranged from 100 µm to 150 µm.

Chemically-selective images were processed by using the custom software from

Thermo (ImageQuest 1.0). Chemical abundance information was presented using either

absolute intensity values or normalized intensity values. The fractional peak intensity for the

peak of interest compared to the total ion current (TIC) of each mass spectrum was used for

normalized intensity. The mass window was from 0.8 Da to 1.0 Da.

Mass spectral imaging and image processing of flowers and stem sections. 50 µm

spacing was used for whole flower imaging and stem section imaging (oversampling).

Because of the need of complete ablation for oversampling technique 51, two methods,

selective spectra averaging and whole spectra averaging, were applied for MS imaging of

Arabidopsis flowers. Images of flowers in this article were processed with whole spectra

averaging. Experimental details of selective spectra averaging and comparison between two

methods are described in Supporting Information, and chemically-selective images from

61

Arabidopsis flower by selective spectra averaging is shown in Supporting Information Figure

S2.

Whole spectra averaging without complete ablation was designed to generate similar

MS images to those with complete ablation. Under our experimental conditions, more than

one order of magnitude decrease in normalized intensity of mass spectra was observed after 5

to 8 microscans (one microscan corresponds to getting one mass spectrum from the sample).

Therefore, a fixed number of microscans (5 for Arabidopsis flowers) was preset and data

were collected for one x,y-coordinate. All microscans were averaged and images were

generated by using the custom software from Thermo (ImageQuest 1.0).


Mass spectral profiling and imaging of metabolites from Arabidopsis leaves.

VLCFAs were readily detected as deprotonated ions ([M – H]–) from the surface of

Arabidopsis leaves (Figure 2) using GALDI in the negative-ion mode. Consistent with

previous, traditional extraction-based analyses 39, 52, 53, our analyses showed C26, C28, and

C30 fatty acids (FAs) as the most abundant such analytes on the surface of Arabidopsis

leaves (Figure 2). However, ions from flavonoid compounds were not consistently detected

from Arabidopsis leaves. After examination of the leaves used for the MS analysis, we found

that ions from flavonoids were readily detected only from the portion of leaves that were

damaged during handling when they were attached to the MS sample plate. In contrast, when

leaves were attached to the plate using air pressure to avoid damage, no ions from flavonoids

were detected (Figure 2). Because flavonoids are typically intracellular metabolites and

VLCFAs are constituents of epicuticular waxes, these results indicate that the penetration

depth of the laser is shallower than the thickness of the epicuticular wax layer of the leaf.

To confirm this observation, chemically-selective images of the partially chloroform-

dipped leaf were collected using GALDI MS. Dipping the leaf in chloroform removes the

62

surface epicuticular waxes. As shown in Figure 3, ions corresponding to VLCFAs showed

high abundance in the area of the leaf that was not dipped in chloroform, especially on the

central vein of the leaf, whereas the abundance of these ions was very low in the area of the

leaf that was dipped in chloroform. In contrast, ions specific for kaempferol (at m/z 285), and

kaempferol rhamnoside (at m/z 431) were detected mostly from the chloroform-dipped area

and from the area in which the intact leaf was grasped with forceps. Thus, minimizing

physical stress on the sample surface is critical to avoiding artificial information about the

spatial distribution of metabolites.

Intense signals at m/z 226, 210, and 194 were observed in the chloroform-dipped area.

Mass spectral profiles and chemically selective images for m/z 226 and 194 are shown in

Supporting Information Figure S1. Images for ions at m/z 226 and 194 which are 16 Da away

from ions at m/z 210 have the same specific pattern that is similar to the venation pattern of

the leaf even after chloroform dipping (see Supporting Information, Figure S1). These data

indicate that it should be possible to profile internal compounds by the chemical removal of

the surface layer from the plant sample while preserving the subsurface spatial information.

Such is not possible in conventional imaging MS. Further studies will be needed to verify

this observation, since the specific solubility of the targeted compounds and the dipping time

are expected to affect their removal and redistribution. Conceptually, depth profiling by serial

data collection can probe deeper and deeper into the tissue but additional colloidal graphite

sprayings are needed because of the decrease of signal intensities after serial collection. In

addition, ablating by laser has much smaller penetration depth than chemical extraction.

Therefore, it will take much longer time to access the same depth as that after chemical

extraction.

Mass spectral profiling of flavonoids from Arabidopsis flower. Similar to leaves,

no flavonoids or only a low apparent abundance flavonols were detected from the surface of

flower carpels or sepals. In contrast, flavonoids were easily detected from petals as highly

63

intense signals. Based on the mass spectral profile from petals and the product ion spectra for

the major peaks in this profile, at least 14 flavonoid species could be classified and identified.

These ions are listed in Table 1 with possible structural identities, and representative product

ion spectra for ions at m/z 609 and 623 are shown in Figure 4. These species basically

comprised of three different flavonols aglycones-kaempferol (K), quercetin (Q), and

isorhamnetin (I)- and their mono-, di- and triglycosides. There are some other observed ions

which correspond to other flavonol aglycones. However, in Table 1, we listed only three

flavonols and their derivatives that were thoroughly investigated by our own MSn results and

showed reproducible signals through flower by flower, or organ by organ. In GALDI MS,

flavonoids were putatively identified as follows: First, MSn experiments were performed up

to the third generation product ion spectra (n=4). Second, fragmentation patterns were

comprehensively compared with those from all available standards or with literature data.

Most product ion spectra clearly show the identity of the flavonol aglycone and the

composition of sugar moieties. In Figure 4A, for example, fragment ions at m/z 315, which

corresponds to the molecular ion of the flavonol isorhamnetin ([I - H]–), were generated after

the neutral loss (NL) of 162 Da and of 146 Da which correspond to the elimination of hexose

(Hex) residue and rhamnose (Rha) residues from parent ions at m/z 623. This series of NLs

and fragment ions show that the composition of ions at m/z 623 is I-Rha-Hex. Unlike LC-MS

and NMR techniques for flavonoid analyses 44, 45, 54-57, direct profiling by LDI MS does not

include a separation step. Therefore, there is a possibility of the presence of two or more

isobaric species at one m/z peak. In the first generation product-ion spectrum for the

precursor ions at m/z 609 (Figure 4B), the combination of NL(i), NL(iii), and the fragment

ion at m/z 285 corresponds to the composition K-Hex-Hex. In contrast, the combination of

NL(iii), NL(v), and the fragment ion at m/z 301 corresponds to the composition Q-Rha-Hex.

To overcome difficulties associated with isobaric ions, separating isobaric ions by detecting

their different specific fragment ions by tandem MS imaging may be needed 24, 25.

64

Interestingly, mass spectral profiles generated from a single petal changed

dramatically depending on the locations where the mass spectra were collected (Figure 5). By

matching structural compositions in Table 1 with m/z values of the dominant species at the

tip of the petal (Figure 5A), kaempferol and its glycosides were found to be much more

abundant over the other two flavonols and their derivatives, while the dominant species close

to the flower base (Figure 5C) are quercetin (Q), isorhamnetin(I), and their glycosides. The

spatial distribution of flavonols and their glycosides are further discussed in the following

mass spectral imaging section.

Mass spectral imaging of flavonoids from Arabidopsis flowers. As shown in

Figure 5, mass spectral profiles change dramatically within a single flower petal. To confirm

this observation that flavonoid accumulation is spatially heterogeneous in petals, chemically-

selective images for ions of flavonoid species were generated. As expected, Figure 6 shows

the difference in spatial distributions of three flavonols and their sugar moieties. It should be

noted that local distributions of flavonols (at m/z 285, 301, and 315) shown in Figure 6 are

not only from flavonol aglycones themselves but also from their glycosides because favonol

glycosides also produce ions corresponding to flavonol aglycones as fragment species by the

laser- induced fragmentation. However, the degree of this fragmentation in our sampling

environment (0.17 Torr) is usually much lower than in high vacuum environment (~10-6

Torr) 58, 59. In addition, the relative abundances of isobaric ions with different compositions at

each m/z can be estimated based on the images, although the relative abundances of isomers

with the same composition cannot be distinguished by mass spectral images. According to

Table 1, isobaric ion species may exist at m/z 447 (Q-Rha and K-Hex), 593 (K-Rha-Hex and

Q-Rha-Rha), and 609 (Q-Rha-Hex and K-Hex-Hex). By comparing locations with abundant

flavonol aglycones with those of isobaric ion species in Figure 6, higher abundances of Q-

Rha at m/z 447, K-Rha-Hex at m/z 593, and Q-Rha-Hex at m/z 609 can be expected. Among

flavonol glycosides which have the same flavonol aglycone, sub-localization of their

65

glycosides was observed in one abundant area. The ion species at m/z 755, which

corresponds to quercetin triglycosides (Q-Rha-Rha-Hex), was observed to be highly

localized around the boundary between kaempferol-localized area and quercetin-localized

area.

The heterogeneous distribution of flavonoid compounds within a single petal of an

Arabidopsis flower has never been reported or visualized in any previous studies.

Simultaneously probing metabolite location and chemical composition by using imaging MS

makes it possible to expand our understanding of biological synthetic pathways of secondary

metabolites in plants. The data presented here can be combined with a series of studies about

flower development 60, 61 and biosynthetic pathways of flavonoids 46, 47, 62, 63. In particular, the

spatial distribution of these flavonol compounds suggests that genetic regulation for

expressing enzymes involved in flavonoid biosynthesis, such as flavonoid 3′-hydroxylase

(F3′H) which converts kaempferol to quercetin by catalyzing the hydroxylation at the 3′

position in the B-ring of the flavonol 43, 64-68 and flavonol glycosyl transferase (FGT) which is

responsible for transporting sugar units to the specific hydroxyl groups of the flavonol 47, 69,

may be a time-dependant process during maturation of the Arabidopsis flower.

The ability of GALDI MS imaging and profiling shown above can also be applied to

rapid screening and metabolite profiling of mutants which are related to the biosynthesis of

flavonoids such as the transparent testa mutants.43 Combining the high spatial resolution

metabolite imaging with the mutant screening by GALDI MS has the potential to provide a

new direction to functional genomics studies.

Figure 7 shows chemically-selective images generated from the whole flower. Higher

abundances of flavonols and their glycosides on the petal surface compared to other parts of

the flower surface and consistency of the localization of flavonols through petals are clearly

depicted. In addition to flavonoids, high abundances of C29 ketone (at m/z 421) and C30 FA

(at m/z 451) were observed in a carpel and a flower pedicle, which is consistent with previous

66

studies 38-40, 53. We also found several unknown compounds including ions at m/z 978 that

were highly localized on the carpel surface. Interestingly, intense signals from ion species at

m/z 717 were observed at the stigma. This species has not been unambiguously identified,

however, its spectra aresimilar to those of condensed tannin compounds 12, 70 based on its

fragment ions (m/z 602, 339, 311, 309, 291, and 247).

It should be noted that images of those ion species that were found mainly at the

carpel and the stigma were processed with normalized intensities instead of absolute

intensities. The reason is that the average intensities from the carpel (~104) is about 10 times

lower than those from petals (~105) such that the spatial distribution at the carpel becomes

difficult to distinguish from background signals of the petal area if these ions were processed

with absolute intensities. This difference in ion yield may come from several inherent factors

such as different shape and thickness of flower parts and different surface characteristics due

to the different cuticular wax load of each flower part. Therefore, quantitative comparison

among different flower organs is limited in the direct profiling of metabolites by LDI MS.

Because total ion current is influenced directly by ion yield, normalized intensities by TIC

were considered as a reasonable processing approach in this case. In addition, different

classes of compounds are difficult to compare quantitatively even if their ions are generated

from the same sample surface due to their different ionization efficiencies. In other words,

comparing the apparent amounts of flavonoids with those of cuticular wax compounds does

not give reliable quantitative estimates.

Light–induced flavonoid accumulation in Arabidopsis stems. Flavonoid

accumulation in the stem under the high fluence of photons was chosen as a model system

for demonstrating the utility of GALDI MS imaging method. After 14 days of light treatment,

stem sections were imaged and compared to images of stem sections from control plants

(Figure 8 and 9). As shown in Figure 8, light-treated Arabidopsis stems accumulate

anthocyanin pigments and become dark purple in color (Figure 8b). Here we used two

67

histochemical staining techniques (DMACA and DPBA staining) to determine flavonoid

localization in tissue and cells in Arabidopsis stem cross-sections as revealed by bright-field

light microscopy and epi-fluorescence microscopy (Figure 8c-8f) 48, 71. DMACA is highly

sensitive and selective for flavonols50: a blue to purple-brown color (Figure 8d, shown with

black arrows) is produced. The dark-blue DMACA stain showed sieve-tube elements with

large amounts of flavanols in vacuoles (black arrows in Figure 8d). Flavonoid accumulation

was visualized in vivo by using DPBA histochemical stain via fluorescence (white arrows in

Figure 8e and 8f). Thus, although transmission or fluorescence microscopy provides high

spatial information concerning the location of ‘colored’ compounds such as flavonoids, it

lacks the ability to decipher chemical identification. On the other hand, the mass spectral

images in Figure 9 show obvious areas where kaempferol at m/z 285 and their

monoglycosides at m/z 431 preferentially accumulate in light-treated stem sections as

compared to control stem sections. Another interesting observation is that the intense signals

at m/z 749 and 765 were observed only in light-treated stem sections and their distribution is

different from that of kaempferols. Based on fragment ion patterns (data not shown), these

may be similar to substructures of the end product, proanthocyanidin (PA). This result

suggests that GALDI MS profiling and imaging can simultaneously provide spatial

distribution on plant tissue sections like microscopy and chemical identities like LC-MS.

However, the current spatial resolution (50-100 µm) is not high enough to differentiate cell

by cell in epidermis, and sampling areas with diameters in the low micron range must be

developed to achieve cell-to-cell comparison similar to light microscopy techniques.

Acknowledgement

E.S.Y. thanks the Robert Allen Wright Endowment for Excellence for support. H.I.I.

thanks the National Science Foundation for support under MCB-0416730 and MCB-0520140.

The Ames Laboratory is operated for the U.S. Department of Energy by Iowa State

68

University under Contract No. DE-AC02-07CH11358. This work was supported by the

Director of Science, Office of Basic Energy Sciences, Division of Chemical Sciences.

Appendix

Further experimental consideration about enhancing spatial resolution in mass

spectral imaging by ‘Oversampling’ was discussed in Appendix 3.

Table 1. Observed flavonoid compounds by GALDI MSn from Arabidopsis thaliana wild type (Col) flower

m/z values

[M–H]–

Observed major m/z values of

fragment ions (NLs) Compositionb Possible structural identities References

285 151, 179, 229 Kaempferol (K) Kaempferol

301 151, 179, 229, 285 Quercetin (Q) Quercetin

315 151, 179, 228, 300 Isorhamnetin (I) Isorhamnetin 72

431 285(146), K-Rha

447 285(162), 301(146) Q-Rha and K-Hex Quercetin-3-O –rhamnoside and

Kaempferol-3-O – glucoside

55

461 315(146) I-Rha

463 301(162) Q-Hex Quercetin-3-O – glucoside 56

477 315(162) I-Hex

577 285, 429, 431(146) K-Rha-Rha Kaempferol-3, 7-di-O -rhamnoside 44

593 285, 327, 429, 431(162), 447(146) K-Rha-Hex and

Q-Rha-Rha

Kaempferol-3-O -glucoside-7-O-rhamnoside

and Quercetin-di-rhamnoside

44, 54

609 285, 301, 429(180), 447(162), 463(146) Q-Rha-Hex and K-Hex-Hex Quercetin-glucoside-rhamnoside 54

623 315, 461(162), 477(146) I-Rha-Hex

739a 284, 430(309), 447, 593(146) K-Rha-Rha-Hex Kaempferol-3-O –

rhamnoside(1→2)glucoside-7-O-rhamnoside

55, 73

755 301, 447, 609(146) Q-Rha-Rha-Hex Quercetin- 3-O – rhamnoside-glucoside-7-O-

rhamnoside

57, 74

a: Fragment ions from both 1st generation and 2nd generation (739→593→) product ion spectra were included

b: K: Kaempferol, Q: Quercetin, I:Isorhamnetin, Rha: rhamnoside, and Hex: hexoside (galactose or glucose)

69

70

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Figure Captions

Figure 1. Structures of flavonol aglycones and glycosides. Arrows indicate hydroxyl

groups that are modified by glycosylation.

Figure 2. Negative-ion mode GALDI mass spectrum taken from an Arabidopsis leaf.

Mass spectra from 45 scanning points on the leaf central vein were averaged.

VLCFAs which have 24 to 30 carbons were detected. C24, C26, C28, C30

FAs correspond to tetracosanoic, hexacosanoic, octacosanoic, and

triacontanoic fatty acids.

Figure 3. An optical image of chloroform-dipped leaf (upper center) and chemically-

selective images of major compounds. Dimension of the image is 7600 µm

high × 14100 µm wide. The step size for data collection was set to 150 µm for

both x and y directions. C26 and C30 fatty acids showed high abundance on

untreated area (right column) while kaempferol and its monoglycoside

showed high abundance in forcep-grasped area and chloroform-dipped area

(left column). Ion species at m/z 210 showed very high abundances in the

dipped area (lower center). Mass spectral profile of the dipped area is shown

in Supporting Information Figure S1. All mass spectral images shown here

were presented as normalized intensities and maximum scale values for

kaempfeol, kaempferol rhamnoside, ions at m/z 210, C26 fatty acid, and C30

fatty acid were set to 2.5%, 3%, 10%, 5%, and 3% of total ion current (TIC)

value, respectively. All images were smoothed linearly.

76

Figure 4. First generation product ion spectra of ions detected at (A) m/z 623 and

(B) m/z 609 from the negative-ion mode GALDI mass spectrum of

Arabidopsis petal. The neutral loss of 146 Da (NL 146) corresponds to the

elimination of a rhamnose moiety and NL 162 corresponds to the elimination

of a hexose moiety. The loss of 163 Da corresponds to the elimination of the

radical C6H11O5°. NL 180 corresponds to subsequent water loss after NL 162.

Fragment ions at m/z 315 and m/z 285 correspond to deprotonated ions of

isorhamnetin(I) ([I – H]-) and kaempferol(K) ([K-H]-), respectively. Chemical

compositions corresponding to ions (A) m/z 623 and (B) m/z 609 are listed in

Table 1.

Figure 5. Mass spectral profiles from three locations in an Arabidopsis petal. The

optical image on the left side is the image of the whole flower which was

attached to the sample plate. The image was taken inside the mass

spectrometer before spraying colloidal graphite onto the flower. The image on

the right side is the magnified view of the petal. Dimensions are 4900 µm high

× 5200 µm wide for the whole flower image and 2822 µm high × 2445 µm

wide for the petal image. Three areas annotated with (A), (B), and (C) indicate

where the mass spectra were collected. Each area contained 50 rastering

points and the plots were the averaged mass spectra of 50 rastering points

from each area. Symbol K, Q, and I correspond to the three flavonol

aglycones listed in Table 1 and numbers above the major peaks depict

nominal m/z values listed in Table 1.

Figure 6. Chemically selective images of Arabidopsis petals. Petals in these images are

the same as in Figure 5. The step size for data collection was set to 50 µm for

77

both x and y directions. Dimension of the images is 2822 µm high × 2445 µm

wide. The nominal value in each image corresponds to the nominal m/z value

of the corresponding ions. Chemical compositions of corresponding m/z

values are listed in Table 1. All images were processed with absolute intensity

values and intensity scales were adjusted individually for the best presentation.

The images were not smoothed.

Figure 7. Chemically selective images of Arabidopsis flower. The step size for data

collection was set to 50 µm for both x and y directions. Dimension of the

images is 4740 µm high × 4600 µm wide. The nominal value in each image

corresponds to the nominal m/z value of the corresponding ions. Chemical

compositions of corresponding m/z values were listed in Table 1 except m/z

421(C29 ketone), 451(C30 fatty acid), 978(unknown), and 717(unknown).

Four mass images (421,451, 978, and 717) on the first row were processed

with normalized intensities and the maximum scale values were shown as a

percentage of the total ion current. The other images were processed with

absolute intensity values and the maximum scale value was given for each

image. All images were smoothed linearly.

Figure 8. Effect of light on flavonoid and anthocyanin content and distribution in the

inflorescence stem of Arabidopsis. Left column, grown under normal-light

regime; and right column, grown under high-light regime. (a) and (b),

Stereomicroscopic images of the inflorescence stem. Anthocyanin

accumulation in (b) is shown with stars. Bars: 500 µm. (c) and (d), Bright-

field light microscopic view of inflorescence stem cross-sections using

DMACA staining to show localization of total soluble phenols, soluble

78

flavanols and and proanthocyanidins (PAs): the black arrows show blue-

brown-purple colored sieve-tube elements of phloem cells. Bars: 20 µm. (e)

and (f), DPBA staining viewed by fluorescence microscopy: fluorescence

shows mostly selected flavonoid localization in the collenchyma under the

epidermis as patchy areas. Orange fluorescence (kaempferol and quercetin);

bright-yellow fluorescence (naringenin-chalcone); and chlorophylls red

autofluorescence (shown with white arrows). Ph, Phloem; col, collenchyma

cells; and Xy, Xylem. Bars: 40 µm.

Figure 9. Chemically selective images of Arabidopsis stems grown under normal-light

regime as control (top row) and grown under high-light regime (bottom row).

Step spacing was set to 50 µm for both x and y directions. Sizes of both stem

sections were 1100 ~ 1200 µm in diameter. All images were processed with

normalized intensities and maximum scale values were shown as a percentage

of the total ion current. The accumulation of kaemperols (m/z 285) and its

glycosides (m/z 431) in light-treated stem section is obvious compared to

control stem section. The accumulation of the unknowns at m/z 749 and 765

shows a different local distribution from kaempferols. All images were

smoothed linearly.

79

HO

OH

O

OOH

R

OH

7 3

3'

OH

HO

H

HO

H

HOHH OH

OH

OH

OH

H

OHOH

OHH HH

beta-D-glucopyranose

6-deoxy-alpha-L-mannopyranose (Rhamnose)

R: H (kaempferol)OH (quercetin)OCH3 (isorhamnetin)

Figure 1.

80

Figure 2.

81

C26

ACI

D (m

/z39

5)

C30

ACI

D (m

/z45

1)

Dip

ped

Not

dip

ped

Gra

sped

Kaem

pfer

ol(m

/z28

5)

Kaem

pfer

olRh

amno

side

(m/z

431)

m/z

210

0M

AX

Figure 3.

82

Figure 4.

83

(C)

(B)

(A)

Figure 5.

84

285

301

315

577

609

477

431

463

461

739

447

623

593

755

Figure 6.

85

m/z

285

(1.0

E6)

m/z

431

(5.0

E5)

m/z

593

(3.0

E5)

m/z

739

(5.0

E4)

m/z

301

(3.0

E5)

m/z

315

(1.5

E5)

m/z

477

(1.0

E5)

m/z

609

(1.0

E5)

m/z

421

(5.0

%)

m/z

451

(5.0

%)

m/z

978

(3.0

%)

0M

AX

m/z

755

(4.0

E4)

m/z

717

(0.5

%)

m/z

577

(1.0

E5)

Figure 7.

86

Figure 8.

87

m/z

285

(2.0

%)

m/z

431

(2.0

%)

m/z

749

(1.0

%)

m/z

765

(1.0

%)

0MA

XC

ON

TRO

L

LIG

HT

TREA

TED

Figure 9.

88

CHAPTER 4. DIRECT PROFILING AND IMAGING OF

EPICUTICULAR WAXES ON ARABIDOPSIS THALIANA BY LASER

DESORPTION/IONIZATION MASS SPECTROMETRY USING

SILVER COLLOID AS A MATRIX

Part of this chapter submitted to The Plant Journal*

Sangwon Cha, Zhihong Song, Wenxu Zhou, Basil J. Nikolau and Edward S. Yeung

Abstract

Colloidal-silver laser desorption/ionization (LDI) mass spectrometry (MS) was

employed to profile and image epicuticular wax metabolites in Arabidopsis leaves and

flowers. Mass spectral profiles of wax compounds were recorded directly from various plant

surfaces. Major wax compounds, very long chain fatty acids and their derivatives including

alkanes, primary alcohols, and ketones were successfully detected as silver adduct ions. With

the ability of small-area sampling and the excellent sensitivity, surface species of each flower

part, carpels, petals, and sepals, were profiled for the first time. In addition, mass spectral

profiles and images collected from wild-type and mutants were used for investigating

variations of wax products by normalizing the ion intensities to a reference peak, [107Ag + 109Ag]+. Differences in profiles between wild-type (Ler) and cer mutant (cer2) by LDI MS

were compared with those from GC-MS. We propose that the cer2 gene product may be

involved in either C30 fatty acid to C30 aldehyde reduction or C30 aldehyde to C29 alkane

decarbonylation in the wax biosynthesis pathway. It may also have a location specific

regulatory function.

Introduction

As a barrier to the abiotic environment, plants produce the cuticle which protects

them from external stresses, such as water, insects, and pathogens. The cuticle is composed

89

of two hydrophobic components, cutin and cuticular waxes 1, 2. A fatty acid-based polyester,

cutin serves as the structural backbone of cuticle and is covered and blended with aliphatic

long-chain fatty acids and their derivatives, cuticular wax. Functional genomics and

metabolomics studies on cuticular wax biosynthesis pathway and their transport mechanism

have been carried out mainly with Arabidopsis thaliana and achievements in this field were

thoroughly reviewed recently 3.

Several wax-deficient mutants have been screened mainly by visually examining the

phenotype, and the mutant loci have been identified for Arabidopsis thaliana, eceriferum

(cer) 4. In addition to visual screening, a condensed GC method was employed to screen the

visually identical mutant lines 5, twenty four cer loci have been identified so far. Among

CER genes, CER2 gene has been isolated and characterized by Xia et al. 6. And they

suggested that CER2 gene encodes a 47 kDa, nuclear localized protein 7. However, the

function of CER2 gene product is still unknown 3.

The wax profiles of cer mutants have been analyzed by gas chromatography mass

spectrometry (GC-MS) and, based on differences in the carbon-chain lengths and the

amounts of wax constituents, the function of cer genes and their products that are involved in

wax biosynthesis were putatively identified 5, 8-16. GC-MS methods are always concomitant

with chemical extraction of the wax compounds by organic solvents and derivatization with

volatile functional groups such as trimethylsilane groups. Therefore, these profiling

procedures are labor-intensive and the sample sizes are limited by the extraction protocol and

by the sensitivity of GC instrumentation. In addition, chemical extraction cannot be

exclusively restricted to epicuticular waxes and the degree of extraction is also ambiguous.

Recently, laser desorption/ionization mass spectrometry (LDI MS) has been

employed to analyze various wax compounds and alkane oligomers 17-20. In these studies,

silver-based matrixes yielded adduct ions for alkanes and their derivatives. The other

advantage of silver-based matrixes over other transition metal-based matrixes is that the

90

reactivity of silver to alkanes is lower than that of any other transition metals. Therefore,

silver mostly generates intact silver adduct ions without fragmentation 21. Recently, direct

LDI-MS analysis of wax compounds on Arabidopsis stems and leaves by using silver colloid

as a matrix was successfully performed 22. The advantage of colloidal silver over other silver

matrixes, such as ultrafine silver powder, silver nitrate, and AgTFA is that colloidal silver

solution can be applied more easily and more homogeneously onto hydrophobic surfaces

than other silver matrixes. Since it does not form crystals when it dries, good reproducibility

of the mass spectral signals can be expected, making it possible to examine localization of

the compounds of interest on the plant surface. In other words, colloidal silver is well suited

for imaging MS.

Here we extend the application of colloidal silver-LDI MS for the analysis of plant

cuticular wax. By rastering over the plant material, mass spectral profiles and chemically-

selective images were successfully generated for Arabidopsis leaves and flowers. After

normalization of the mass spectra with respect to the reference peak, reliable relative

abundance information was obtained that can be compared with traditional GC-MS analysis.

Compositional variations between wild-type and cer2 mutant flower parts were investigated

for the first time by silver-LDI MS and GC-MS analysis of whole-flower wax metabolites

was also performed whereas most of the previously reported metabolite profiling were

focused on leaf and stem 10, 16.


Chemicals. Standards such as n-alkanes, alcohols, esters, ketones, and fatty acids,

consisting of 13–32 carbon atoms, BSTFA/TMCS (N,O-Bis(trimethylsilyl)trifluoroacetamide

with trimethylchlorosilane), and MS media (Murashige and Skoog basal salt mixture) were

obtained form Sigma-Aldrich (St. Louis, MO). A mixture of n-alkanes (C12–C60) was

purchased from Supelco (Bellefonte, PA). Water-based colloidal silver (20 ppm) was

91

purchased from Purest Colloids (Westhampton, NJ). Double-deionized water was used from

a MilliQ water purification system (Framington, MA). All other chemicals were purchased

from Fisher Scientific (Fairlawn, NJ).

Plant growth conditions. Arabidopsis thaliana ecotype Landsberg erecta (Ler-0)

and its eceriferum mutant (cer2) seeds were obtained from the ABRC. Seeds were sown on

MS media in petri dishes. The dishes were placed in the growth room for 10 days after

keeping at 4oC for 4 days. On 15th day the plants were transferred in soil for continuous

growth. Leaves were collected on 26th days, and flowers were collected on 34th days.

Growth room was at 24°C with an illumination at 85 μE m-2s-1 and 100% relative humidity.

Plant sample preparation for LDI mass spectral profiling and imaging. After

collecting samples from plants, plant materials were attached onto a stainless steel target

plate of similar dimensions as a microscope glass slide using a conductive double-sided tape

(3M, St. Paul, MN). To avoid damage to the plant sample surface, contact area by forceps

was minimized and air pressure from a nitrogen gas cylinder was used for attaching samples

firmly onto the sample plate. All samples were dried in moderate vacuum (approximately

~50 Torr) for 30–60 min. As shown in Figure 1, carpels, petals, and sepals were separated

and attached individually for metabolite profiling of flower parts. Three replicates of leaves

and whole flowers, and five replicates of flower parts for each genetic type were prepared.

The spraying device for colloidal silver solution was composed of a computer-

controlled syringe pump with a 500 μL syringe (Kloehm LTD., Las Vegas, NV), MicroFlow

PFA-ST nebulizer (Elemental Scientific Inc., Omaha, NE) with a 0.25 mm i.d. sample uptake

capillary, and a helium gas cylinder. Spraying time and speed was programmed by the

software “WinPump®” which is provided by Kloehm. To obtain a homogeneous coverage of

silver particles, several intervals of spraying with a small volume of colloidal silver solution

were more desirable than one-time spraying with a large volume because silver particles tend

to aggregate when they are dried. Therefore, the parameters for spraying were optimized as

92

100 μL/min flow rate with 12.5 μL of spraying volume, and 8 sets of spraying and air-drying

were performed for each plant sample. The distance between the nebulizer tip and the sample

was 12.4 cm and the area covered by colloidal silver on the sample plate was 4.5 cm2.

Spraying onto the leaf was performed without moving the sample plate because leaf sizes are

much smaller than the spray area.

Plant sample preparation for gas chromatography-mass spectrometry. Twenty

five flowers or whole leaves of a plant were collected and weighed. An aliquot of internal

standard hexadecane was added to the surface of the plant material. The plant material was

completely immersed in chloroform for 60 s. The cuticular wax was extracted and dried

under nitrogen gas. Samples were derivatized using BSTFA/TCMS (65˚C, 30 min) for

GC/MS analysis. 3 replicates of leaves and flowers were prepared.

Mass spectrometry. For LDI mass spectral profiling and imaging, a Thermo

Finnigan LTQ linear ion trap mass spectrometer equipped with vMALDI source (Mountain

View, CA) was used. Fiber-optic guided nitrogen laser (337 nm, maximum energy of 280

µJ/pulse, and maximum frequency of 20 Hz) was used as a laser source. The laser spot size

was 100 µm at the target plate surface. The intermediate-pressure (0.17 Torr) sampling

environment was kept by nitrogen gas flow control and this allows softer ionization

compared to high vacuum environments (~10-6 Torr). All mass spectra were collected in the

positive-ion mode and the scanning range was set to m/z 200 to m/z 1000.

For unknown peaks acquired directly from plant samples, peak identification was

carried out by matching monoisotopic masses with those detected from GC-MS experiment.

For overlapped peaks due to two stable silver isotopes and similar monoisotopic masses, the

major compounds detected were determined by comparing the first generation product ion

spectra from unknown peaks with those from standards or from literature data.

GC-MS analysis was performed with an Agilent 6890 GC interfaced to a 5973 mass

spectrometer (Agilent Technologies). A HP-5ms column (30 m x 0.25 mm i.d. coated with a

93

0.25 µm film, Agilent Technologies) was used, and temperature gradient was programmed

from 80 to 320 °C at 5°C/min with He flow rate at 2.2 mL/min. Operating parameters were

set to 70 eV (electron ionization) for ionization voltage and 280 °C for interface temperature.

The GC-MS data files were deconvoluted by NIST AMDIS software, and searched against

our laboratory’s standard compounds library and the NIST compounds library.

LDI Mass spectra collection for profiling and imaging. For leaves and flower parts,

the number of laser shots and the laser intensity scale were examined by collecting mass

spectra in a small area (usually 5 to 10 rastering points) by turning on the automatic gain

control feature (AGC, which keeps the ion amounts in the trap at a similar range by varying

the number of laser shots) of the mass spectrometer. After optimizing the laser parameters, a

fixed number of laser shots without AGC was used for collecting mass spectra over the

whole sample. For whole flower imaging, however, varying numbers of laser shots that were

controlled by AGC were applied because each flower part has different surface

characteristics and wax loads which can affect ion yields. The sample was scanned with a

step size which ranged from 50 µm to 100 µm.

Mass spectral images for whole flowers were processed by using the custom software

from Thermo (ImageQuest 1.0). The normalized intensity value which is defined as the

fractional peak intensity compared to the total ion current (TIC) of each mass spectrum was

used for presentation of chemical abundance information. The mass window was set to 0.8

Da – 1.0 Da. For comparing relative abundances among samples, intensities relative to the

peak intensity at m/z 215.8 ([107Ag + 109Ag]+) were used.


Silver-LDI mass spectral profiling of metabolites from Arabidopsis leaves. Figure

2 shows the averaged silver-LDI mass spectrum taken from an Arabidopsis thaliana wild

type (Ler) leaf surface. As shown in the inset of Figure 2, the Ag2+ ion at m/z 215.8

94

corresponding to [107Ag + 109Ag]+ showed the highest intensity, and this was consistent

through all mass spectra collected under our experimental conditions. Therefore, the relative

intensity with respect to the peak intensity at m/z 215.8 was used as the intensity scale for

quantification purposes in interpreting the mass spectra of wax compounds.

Because two stable isotopes of silver are present with similar abundances (107Ag:

51.839 % and 109Ag: 48.161 %), each hydrocarbon compound produces a quartet of silver

adduct peaks. This quartet pattern helped to distinguish sample peaks from noise, but the

multiple peaks induced spectral complexity due to the overlap of compounds different by 2

Da in molecular weight. As shown in Figure 2, peaks with odd nominal masses were the

major peaks for the cuticular wax compounds because intensities of the two other isotopic

peaks (due to either 13C or 2H) were much smaller in the mass range where cuticular wax

compounds were detected. Therefore, only peaks with odd nominal masses will be discussed

in this article to simplify the interpretation of the mass spectra. From the mass spectra

collected from Arabidopsis plants, it was hard to identify individual quartet peaks directly

due to overlap, but the m/z ranges which have signals from cuticular wax compounds were

easily grouped as shown in Table 1.

In Table 1, it is obvious that wax load amounts from parallel GC-MS analysis and the

sum of relative intensities from silver-LDI mass spectra according to m/z ranges have a

similar tendency but are not in direct proportion. There are several reasons for this

phenomenon. One of the main reason is the sampling depth by LDI is shallower than that by

the current chemical extraction protocol for GC-MS analysis. Therefore, the silver-LDI mass

spectral profile directly from cuticular wax surfaces does not represent all the cuticular wax

compounds. The shallower sampling depth by LDI may bear the possibility of serial profiling

of cuticular wax compounds according to the depth of the wax layer. For example, plant

sterols and triterpenoids were extracted and constituted about 6 % (~1.5 µmol/g per fresh

weight) of the total wax load. With colloidal silver, plant sterol standards were detected with

95

a very low detection limit, ~200 amol/10000 µm2 (sampling area of the laser). However,

there was no sterol species detected in the LDI mass profiles obtained directly from leaf

surfaces. This indicates that there may be no plant sterols at the outermost epicuticular wax

surface. In addition, as previously reported 22, there are differences in ionization efficiencies

of the wax compounds depending on their functional groups. Therefore, it is difficult to relate

observed intensities directly to actual amounts of wax compounds. In silver-LDI MS, wax

standards which have 18 - 32 carbons showed good peak reproducibility in terms of

intensities but compounds which have smaller carbon number, such as C16 fatty acid, showed

relative intensity variations depending on laser intensities and concentrations. Similar to the

previous report 22, alkanes showed the smallest ionization yields and fatty acids showed the

highest ionization yields for the same molar amount. This observation seems to be consistent

in the wax compound profile. In Table 1, the relative amounts were higher in LDI than those

in GC for m/z regions which contain fatty acid species such as m/z 475 - 477, 503 - 505 and

557 - 561, and the relative abundances were much lower in LDI than those in GC for m/z

regions where major alkanes are present, such as m/z 515-519 and 543-547. Finally, the

relative extraction efficiencies for the different classes of compounds in the GC-MS protocol

are not constant.

Despite overlaps due to silver isotopes and similar molecular weights, many of the

wax compounds in Table 1 can be recognized independently by focusing on one of two silver

isotope adduct ion peaks. In the m/z range of 571-575, for example, C33 alkane and C32

alcohol ion species overlapped each other at m/z 573 as [C33 alkane + 109Ag]+ and [C32

alcohol + 107Ag]+, but each was uniquely detected at m/z 571 as [C33 alkane + 107Ag]+ and at

m/z 575 as [C32 alcohol + 109Ag]+, respectively. However, isobaric ions such as C29 alkane

and C28 aldehyde cannot be distinguished under the current experimental conditions and the

major compounds found in LDI MS among isobaric ions need to be identified putatively by

examining fragmentation patterns in their first generation product ion mass spectra. There,

96

for ion species which contain long chain fatty acids such as m/z 503, 559 and 587 or 589,

losses of water (18 Da) and formic acid (46 Da) were always observed predominantly with

very similar ratios to those observed from fatty acid standards. This may be because of the

high ionization efficiency of fatty acids, but it may also suggest that fatty acids are localized

at the outer cuticular wax layer. For the ion species at m/z 515 and 543 which contain major

alkanes, the fragmentation patterns matched well with those of alkane standards. In spite of

the low ionization efficiency of alkanes, they can be easily detected because the molar

amounts of alkanes in the GC-MS analysis are about 20 to 30 fold higher than isobaric

aldehydes. However, the inability to detect aldehydes separately under the current

experimental conditions (because the reduction steps from fatty acids to aldehydes cannot be

traced by this method) is the main limitation of the silver-LDI MS method. Accurate mass

measurement with high mass resolution could be the solution for this problem. Also, as

indicated in Table 1, unidentified contaminants showed peaks at m/z 533-537. Therefore,

abundance information of C28 fatty acid could not be extracted unambiguously from silver-

LDI mass spectra.

Finally, there were several unknown wax compounds detected in m/z 585 – 673. Two

groups of unknown ion species were found in this m/z range (annotated as ‘Unk-A’ and

‘Unk-B’ in Table 1). Unk-A was detected at m/z 585, 613, 641, and 669 as 107Ag adduct ions

and Unk-B was detected at m/z 597, 625, and 653. Ions in each group are 28 Da away from

each other and this difference corresponds to a C2H4 group. For Unk-B, losses of multiples of

42 Da, which could correspond to propene, were observed and either single loss or quadruple

loss of 42 Da was found as a major fragment ion. For Unk-A, the product ion spectra were

very complicated due to overlap with minor unknown ions.

Comparison of leaf cuticular waxes between wild-type (Ler) and cer2 mutant.

Based on parallel GC-MS cuticular wax results and putative identification of the major

contributing compounds within overlapped isobaric species by tandem MS experiments, wax

97

metabolites that were detected with confidence were summarized in Table 2. For wild-type

(Ler) and cer2 mutant, the relative intensities by silver-LDI MS and the amounts quantified

by GC-MS for corresponding wax metabolites were also shown in Table 2. Ratios of the wax

metabolites were calculated and presented as log2(cer2/Ler) values in Figure 3. From Table 2

and Figure 3, several observations could be summarized. First, all alkanes were detected with

significantly lower intensities or lower amounts from cer2 mutant leaves by both methods.

Second, differences in the amounts of primary alcohols between wild-type and cer2 mutant

were less significant than among other classes of compounds in both methods. Third, from

the silver-LDI MS results, C24 and C26 fatty acids showed significantly smaller intensities in

cer2 than in wild-type, but longer chain length fatty acids, C30 and C32 fatty acids, were

found as more abundant in cer2 than wild-type leaves. In GC-MS analysis, however, all fatty

acids showed a small increase in cer2 mutant. This may also suggest the possibility of

differential integration of fatty acids according to the depth of the cuticular wax layer.

Discussions about the function of the cer2 gene product are given in the last section by

combining the observations above with the results from flower parts.

Silver-LDI mass spectral imaging of Arabidopsis whole flower. For

demonstrating mass spectral imaging as a rapid metabolite profiling tool, a flower was

chosen among Arabidopsis plant organs because flowers are composed of several sub-parts

that have small dimensions, such as carpel, petal, sepal, and stamen. Mass spectral images of

wild-type (Ler) flowers are shown in Figure 4. Because different flower organs have different

surface characteristics and wax loads, the total ion current (TIC), which is directly affected

by ion yields, varies among the flower organs. Therefore, all chemically-selective images for

whole flowers were processed as a normalized intensity defined as the fractional peak

intensity compared to the TIC of each mass spectrum. In Figure 4, the ion species at m/z 529,

which mainly corresponds to [C29 ketone + 107Ag]+, was found as highly localized at the

flower stem and the carpel. Major alkane species, such as [C29 alkane + 107Ag]+ and [C31

98

alkane + 107Ag]+ at m/z 515 and 543, respectively, were found at all three organs as the

major species but they showed relatively low abundances in the tips of petals. Two major

wax compounds, C31 alkane and C30 alcohol, contribute to mass signals in the m/z range 543

– 547. Both wax compounds contributed the intensity at m/z 545 as [C31 alkane + 109Ag]+ and

[C30 alcohol + 107Ag]+. This overlapped image was clearly separated into two images by

choosing different silver isotope ions, i.e. [C31 alkane + 107Ag]+ at m/z 543 and [C30 alcohol + 109Ag]+ at m/z 547, as shown in Figure 4. From the images for m/z 543 and 547, it is clear that

the intensity at the petals and at the center part of the sepals for m/z 545 is mainly from C31

alkane, not C30 alcohol. At the tips of petals, fatty acids ([C18:3 fatty acid + 107Ag]+ and [C26

fatty acid + 107Ag]+ at m/z 385 and 503, respectively) were found at higher amounts than

other wax compounds.

For comparing wax compositions between wild-type (Ler) and cer2 mutant, serial

mass spectral images were generated with a 0.8 Da mass window and a 2.0 Da step size for

the m/z ranges where wax compounds were detected, and chemically selective images for

four m/z values that showed distinct differences between wild-type (Ler) and cer2 mutant

were shown in Figure 5(A). In figure 5(A), it is obvious that C29 alkane and C29 ketone ([C29

alkane + 107Ag]+ and [C29 ketone + 107Ag]+ at m/z 515 and 529, respectively) showed much

lower abundances in cer2 mutant than in wild-type. In contrast, C30 and C32 fatty acids ([C30

fatty acid + 107Ag]+ and [C32 fatty acid + 109Ag]+ at m/z 559 and 589, respectively) showed

higher abundances in cer2 mutant than in wild-type. Interestingly, as clearly visualized in

Figure 5(B), both fatty acids showed high abundances at the tip of the petal, while in the

carpel only C30 fatty acid was found in high abundance.

Silver-LDI mass spectral profiling of Arabidopsis flower parts. Imaging whole

flowers can provide information about wax load variations between wild-type and mutants

with localization information in a very short time, but there are also limitations. Even if

whole flowers are flattened and attached onto the mass spectrometer sample plate with extra

99

care, overlaps among flower organs cannot be avoided. In addition, the degree of wax

variation between wild-type and mutants was hard to recognize accurately by processing

images with normalized intensities. Therefore, profiling wax compounds with individual

flower parts and comparing their mass profiles based on relative intensities to the reference

peak at m/z 215.8 ([107Ag + 109Ag]+) were more desirable. Three major parts of Arabidopsis

flowers, carpels, petals, and sepals were prepared separately and mass spectra were collected

serially from these parts with a 50 µm step movement. The averaged mass spectra for three

flower parts of wild-type (Ler) and its cer2 mutant are shown in Figure 6 and more detailed

peak identifications with abundances for these flower parts are listed in Table 3. In contrast

to leaf wax profiling, peak identification was more straightforward because fewer silver

adduct ion peaks were observed per flower part. Also, the major silver adduct ion peak

pattern was a quartet which corresponds to only one wax compound. As discussed previously,

the relative intensities for each class of compounds are different. In particular, intensities

corresponding to fatty acids were significantly higher. Therefore, to assess the total wax

loads between wild-type and mutants, comparing the sum of intensities from C27 or higher

alkanes, that are known to be the most abundant wax metabolites 3, is more appropriate than

comparing the total intensities from all classes of wax metabolites. As shown in Table 3, the

sum of intensities from C27, C29, and C31 alkanes was higher in wild-type than in cer2 mutant

throughout all three flower parts. Therefore, it is obvious that a global reduction of wax loads

in cer2 mutant exists. However, for carpels and petals, C31 alkane showed a higher

abundance in cer2 mutant than in wild-type.

In the carpel (Figure 6(A) and Table 3(A)), C29 alkane at m/z 515 and C29 ketone at

m/z 529 were detected as the major wax metabolites in wild-type (Ler), as expected from the

whole flower imaging results. However, in cer2 mutant, the relative intensities for these

metabolites were lower by about 5.5 fold. In contrast, the relative intensity for C30 fatty acid

at m/z 559 was higher by about 4.0 fold in cer2 mutant. In the petal (Figure 6(B) and Table

100

3(B)), peaks corresponding to C18:3, C24, C26 fatty acids (at m/z 385, 475, and 503,

respectively) and C29 alkane at m/z 515 showed high abundances in wild-type (Ler). However,

in cer2 mutant, the relative intensities for all major peaks in wild-type (Ler) were lower by

more than 2.6 fold. In contrast, the longer fatty acids, C30 and C32 at m/z 559 and 589,

showed about 4.8 fold higher intensities for cer2 mutant. In the sepal, (Figure 6(C) and Table

3(C)), C29 and C31 alkanes and C28 and C30 alcohol were detected as major peaks in wild-type

(Ler) and the wax metabolite profile was similar to that from the leaf. In the cer2 sepal, the

major differences from the wild-type sepal were lower intensities for C29 alkane (~ 6.5 fold),

C29 ketone (~ 3.5 fold), and C26 fatty acid (~ 5.7 fold). However, C30 fatty acid and alcohol

showed increases in the cer2 sepal. Interestingly, unknown wax metabolites were detected

for both wild-type and mutant at the sepal and showed lower abundances in the cer2 mutant.

GC-MS wax metabolite profiling for the whole flower were performed and results are shown

in Figure 7. The major difference from GC-MS wax metabolite profile for leaves was that no

aldehydes were detected in whole flower analysis.

It should be noted that at least 75 whole flowers (25 flowers per sample and 3

replicates) were needed to get reproducible wax metabolite profiles from GC-MS, whereas,

in silver-LDI MS profiling, only 5 flowers were used for collecting the wax metabolite

profiles of each kind of flower part.

To compare the variations of each wax metabolite, ratios of metabolites in wild-

type(Ler) and cer2 mutant flower parts were presented in Figure 8. Several features from

silver-LDI MS could be summarized and compared with GC-MS results. First, C30 and C32

fatty acids showed higher abundances in cer2 mutant than in wild-type for all flower parts.

The increase in C30 fatty acid was most pronounced in the petal in terms of both intensities

and ratios. This increase was also observed in whole-flower analysis by GC-MS. However,

similar to the results from leaf analysis, C24 and C26 fatty acids were lower in amounts from

silver-LDI MS for all cer2 mutant flower parts whereas they were at about the same level or

101

even higher amounts from GC-MS of cer2 mutant flowers. Second, C29 ketone was obviously

lower in all cer2 mutant flower parts and the decrease was the largest at the carpel in terms of

both intensities and ratios. The decrease in C29 ketone was also seen in GC-MS results. Third,

for primary alcohols, their changes were less obvious than the other classes of wax

compounds for flower parts. This was also consistent with GC-MS results. Fourth, C27 and

C29 alkanes were significantly lower in cer2 mutant flowers. However, C31 alkane showed

the smallest decrease in ratio at cer2 sepals and even increased in cer2 carpels and petals. In

GC-MS results, C31 alkane showed the smallest change in ratio among alkane species. It

should be emphasized that GC-MS results are from whole flower waxes and not from a

single organ. Therefore, differential wax load changes from flower part to flower part cannot

be recognized by GC-MS experiments.

Prediction of regulation of wax synthesis by cer2 gene product. By combining the

observations from leaves and flower parts with known cuticular wax biosynthetic pathways

for Arabidopsis thaliana, we propose that cer2 mutation may be involved either in the C30

fatty acid to C30 aldehyde reduction pathway, as had previously suggested for cer13 by

Rashotte et al. 16, or in the C30 aldehyde to C29 alkane decarbonylation pathway. Because

aldehydes were not readily detected from flower parts, deciding between the two pathways

mentioned above was not possible based only on silver LDI MS profiling. Similar to wax

load changes of cer13 mutant stems (16, levels of C29 products, C29 alkane and C29 ketone,

were lower and levels of C30 primary alcohol are higher in cer2 mutant for all flower parts

and leaves. This is also consistent with GC-MS results. . In addition, accumulation of C32

fatty acid was observed in petals which may be caused by further elongation of the

accumulated C30 fatty acid. However, increases of C31 alkane amounts were only observed in

carpels and petals but not in sepals and leaves. The degrees of increases for C30 fatty acid in

cer2 mutants were much larger in carpels (~4 fold) and petals (~4.8 fold) than in leaves (~1.2

fold) and sepals (~1.4 fold), so lower amounts of subsequent elongation from C30 to C32 fatty

102

acid can be expected in sepals and leaves. Therefore, the relatively smaller amounts of C30

fatty acid in cer2 sepals and leaves may not compensate for the general wax load reduction in

cer2 mutants and cause decreases in C31 alkanes in cer2 sepals and leaves. However, there is

also the possibility of differential regulation of elongation from C30 to C32 fatty acid by cer2

gene product according to flower parts and leaves that is similar to differential regulation

between the stem and the leaf 10.

Conclusions

Wax metabolite profiling by LDI MS with colloidal silver as a matrix has several

advantages over GC- MS approaches. First, sample preparation is much simpler because it

does not require any extraction and derivatization steps. Second, the amounts of samples

required are about 20 to 25 times smaller than those in GC-MS. Third, localization

information of cuticular waxes can be preserved because of the direct sampling capability.

With the use of homogeneous colloidal silver coating on plant surfaces, wax metabolite

distributions on each flower part was successfully profiled for the first time. However, there

are still challenging issues in this method. Overlap due to isobaric ions, especially alkanes

and aldehydes, needs to be resolved to provide more accurate measurements of changes in

wax profiles. It may be solved by employing exact mass measurements with high mass

resolution. In addition, different ionization efficiencies for different class compounds make it

difficult to compare actual abundances between two different classes of wax metabolites

directly from the mass spectra. This may be resolved by systematic studies on response

factors as a function of metabolite classes and sizes. Last, because a mass spectral database

of metabolites for silver LDI-MS does not exist currently, identification of wax compounds is

less certain than GC-MS.

By performing reproducible spraying of colloidal silver solution onto the plant

sample surface by the finely-controllable spraying device, homogeneous and constant surface

103

coverage of colloidal silver particles was achieved. This made it possible to use the intensity

of silver dimer ions as a reference to normalize all mass spectra. In this way, comparison of

the relative wax abundances between wild-type and mutants was successfully made. Wild-

type/mutant wax profile comparisons based on silver-LDI MS results generally showed good

agreement with those based on GC-MS results. However, major variance was present

between the two methods, especially for C26 and smaller fatty acids. It may be because of

sampling depth differences and further investigation is needed to identify this bias.

Lastly, a data processing scheme for the rapid comparison between wild-type and

mutant can be proposed as shown in Figure 9. The basic idea involves two general rules. First,

the two largest peaks in a quartet pattern have about the same intensities because of the

similar natural abundances of the two silver isotopes. Second, changes in the two adjacent

peaks should be similar if only one metabolite is associated with this change. Figure 9 shows

the potential of the silver-LDI MS method as a high-throughput mutant screening tool. Future

work would involve verification of this scheme with a larger data set.

Acknowledgement


Ames Laboratory is operated for the U.S. Department of Energy by Iowa State University

under Contract No. DE-AC02-07CH11358. This work was supported by the Director of

Science, Office of Basic Energy Sciences, Division of Chemical Sciences.

104

Table 1. Possible wax compounds in Arabidopsis thaliana wild type (Ler) leaves according

to mass-to-charge ratio ranges where wax compounds were detected by silver-LDI MS

m/z range Possible ion species a Wax loadc (nmol/g fresh weight)

LDI Relative Intensity (%)e

361-365 C16:1 fatty acid (361) C16:0 fatty acid (363) Unknown contaminant (363)

245.83 ± 39.88 455.39 ± 108.81

dn.a. f4.45 ± 0.53

385-393 C18:3 fatty acid (385) C18:2 fatty acid (387) C18:1 fatty acid (389) C18:0 fatty acid (391)

dn.d. 87.74 ± 18.10

571.67 ± 102.37 119.34 ± 41.54

14.18 ± 0.36

475-477 C24 fatty acid (475) 28.74 ± 3.64 9.85 ± 1.09

487-491 C27 alkane (487) C26 aldehyde (487) C26 alcohol (489)

1141.48 ± 46.00 33.13 ± 2.37

171.47 ± 27.50 15.63 ± 1.41

503-505 C26 fatty acid (503) C27 iso-alcohol (503)

92.45 ± 19.20 18.88 ± 2.50 20.33 ± 2.19


8242.73 ± 148.85 403.24 ± 13.63 412.27 ± 47.53

35.97 ± 1.37

529-535 C29 ketone (529) C28 fatty Acid (531) C29 iso-alcohol (531) Unknown contaminant (533)

19.95 ± 1.69 260.95 ± 18.01

11.53 ± 0.58 n.a.

f8.38 ± 0.18


9014.37 ± 378.82 313.13 ± 21.62 118.37 ± 22.01

32.79 ± 1.56

559-561 C30 fatty acid (559) C31 iso-alcohol (559)

12.41 ± 2.52 17.76 ± 1.48 6.07 ± 0.29


3420.03 ± 170.57 132.80 ± 13.35

59.83 ± 6.86 20.50 ± 1.33

585-589 Unk-A1(585) C32 fatty acid (587) 6.63 ± 1.02 6.28 ± 0.23

597-603 Unk-B1(597)b C35 alkane (599) C34 alcohol (601)

n.a. 123.05 ± 17.23

3.79 ± 0.43 14.13 ± 0.77

613-617 Unk-A2 (613) C34 fatty acid (615)

n.a. 4.38 ± 0.41 4.56 ± 0.29

625-629 Unk-B2 (625) n.a. 12.00 ± 1.14

641-645 Unk-A3 (641) n.a. 5.74 ± 0.01

653-657 Unk-B3 (653) n.a. 6.14 ± 0.47

669-673 Unk-A4 (669) n.a. 4.70 ± 0.87

a. Cuticular wax compounds (nominal m/z values of 107Ag adduct ions) listed are from identified compounds in parallel GC-MS analysis.

b. Unk: Unknown ion species. Unknown species were grouped by fragmentation patterns in their first generation product ion spectra.

c. Wax load values are from GC-MS for three replicates with ± standard error d. n.a. : not applicable, n.d.: not detected e. Relative intensity (%) is defined as the fractional intensity of the intensity at m/z 215.8 which corresponds to [107Ag +

109Ag]+, and the values are listed with ± standard error. f. Due to the overlap with unknown contaminants, only the relative intensity at m/z 361 was used for m/z 361-365 and

only relative intensities at m/z 529 and 531 were included for m/z 529-535.

105

Table 2. Major cuticular wax compounds with their abundances in Arabidopsis thaliana

leaves of wild-type (Ler) and cer2 mutant

Class [M + Ag]+ Major ion species Silver LDI (R.I., %)a GC (nmol/g fresh weight)b

Ler cer2 Ler cer2

Alkane C27 487.3 [C27 alkane + 107Ag]+ 6.38 ± 0.69 2.17 ± 0.23 1141.48 ± 46.00 364.72 ± 23.42

C29 515.4 [C29 alkane + 107Ag]+ 10.63 ± 0.39 3.48 ± 0.33 8242.73 ± 148.85 1011.67 ± 53.85

C31 543.4 [C31 alkane + 107Ag]+ 12.65 ± 0.99 7.00 ± 0.28 9014.37 ± 378.82 2202.02 ± 95.96

C33 571.4 [C33 alkane + 107Ag]+ 7.37 ± 0.66 3.71 ± 0.12 3420.03 ± 170.57 132.70 ± 8.32

C35 599.4 [C35 alkane + 107Ag]+ 5.47 ± 0.51 3.33 ± 0.02 123.05 ± 17.23 11.10 ± 0.59

Alcohol C26 491.3 [C26 alcohol + 109Ag]+ 2.63 ± 0.43 2.97 ± 0.60 171.47 ± 27.50 242.22 ± 20.44

C28 519.4 [C28 alcohol + 109Ag]+ 9.01 ± 1.08 7.24 ± 0.64 412.27 ± 47.53 268.81 ± 46.16

C30 547.4 [C30 alcohol + 109Ag]+ 5.25 ± 0.33 9.04 ± 0.95 118.37 ± 22.01 132.73 ± 20.22

C32 575.4 [C32 alcohol + 109Ag]+ 4.01 ± 0.49 5.31 ± 0.44 59.83 ± 6.86 15.69 ± 1.72

C34 603.4 [C34 alcohol + 109Ag]+ 1.26 ± 0.14 2.39 ± 0.09 3.79 ± 0.43 5.33 ± 0.66

Fatty acid C24 475.3 [C24 fatty acid + 107Ag]+ 5.35 ± 0.80 2.74 ± 0.16 28.74 ± 3.64 48.11 ± 6.96

C26 503.3 [C26 fatty acid + 107Ag]+ 10.95 ± 1.62 3.48 ± 0.33 92.45 ± 19.20 223.87 ± 20.64

C30 559.4 [C30 fatty acid + 107Ag]+ 3.71 ± 0.23 4.67 ± 0.10 12.41 ± 2.52 18.80 ± 2.07

C32 589.4 [C32 fatty acid + 109Ag]+ 1.16 ± 0.13 2.50 ± 0.10 6.63 ± 1.02 11.04 ± 1.50

Ketone C29 529.4 [C29 ketone + 107Ag]+ 2.64 ± 0.13 1.42 ± 0.07 19.95 ± 1.69 20.12 ± 2.01

a. Relative intensity (R.I.) (%) is defined as the fractional intensity of the intensity at m/z 215.8 which corresponds to [107Ag + 109Ag]+ and the values are listed with ± standard error for three replicates.

b. Wax load values are from GC-MS with ± standard error for three replicates

106

Table 3. Major cuticular wax metabolites detected for each flower part by silver-LDI MS for

Arabidopsis thaliana wild-type (Ler) and cer2 mutant.

Table 3(A) Carpel

Class [M + Ag]+ ion species R. I.(Ler) (%) R. I.(cer2) (%) Log2(cer2/Ler)

Alkane C29 515.4 [C29 alkane + 107Ag]+ 16.20 ± 0.31 2.93 ± 0.18 -2.47 ± 0.08

C31 543.4 [C31 alkane + 107Ag]+ 3.64 ± 0.09 5.84 ± 0.84 0.68 ± 0.18

Alcohol C28 519.4 [C28 alcohol + 109Ag]+ 3.60 ± 0.17 2.03 ± 0.05 -0.83 ± 0.06

C30 547.4 [C30 alcohol + 109Ag]+ 2.85 ± 0.17 3.04 ± 0.43 0.09 ± 0.19

C32 575.4 [C32 alcohol + 109Ag]+ 2.52 ± 0.36 2.19 ± 0.82 -0.20 ± 0.48

Fatty acid C18:3 385.3 [C18:3 fatty acid + 107Ag]+ 3.24 ± 0.18 3.01 ± 0.70 -0.11 ± 0.29

C24 475.3 [C24 fatty acid + 107Ag]+ 2.60 ± 0.09 1.24 ± 0.12 -1.06 ± 0.12

C30 559.4 [C30 fatty acid + 107Ag]+ 1.86 ± 0.19 7.37 ± 1.09 1.99 ± 0.22

Ketone C29 529.4 [C29 ketone + 107Ag]+ 21.48 ± 0.98 4.22 ± 0.67 -2.35 ± 0.20

107

Table 3(B) Petal



C29 515.4 [C29 alkane + 107Ag]+ 15.87 ± 1.03 6.10 ± 0.89 -1.38 ± 0.18

C31 543.4 [C31 alkane + 107Ag]+ 6.63 ± 0.37 8.97 ± 0.73 0.44 ± 0.12

Alcohol C26 491.3 [C26 alcohol + 109Ag]+ 2.24 ± 0.06 3.07 ± 0.40 0.45 ± 0.16

C28 519.4 [C28 alcohol + 109Ag]+ 4.88 ± 0.17 3.48 ± 0.26 -0.49 ± 0.10

C30 547.4 [C30 alcohol + 109Ag]+ 2.56 ± 0.39 3.32 ± 0.13 0.38 ± 0.19

C32 575.4 [C32 alcohol + 109Ag]+ 1.93 ± 0.36 2.77 ± 0.34 0.52 ±0.26


C24 475.3 [C24 fatty acid + 107Ag]+ 8.45 ± 0.58 2.99 ± 0.24 -1.50 ± 0.13

C26 503.3 [C26 fatty acid + 107Ag]+ 15.63 ± 1.03 4.17 ± 0.48 -1.91 ± 0.16

C30 559.4 [C30 fatty acid + 107Ag]+ 3.87 ± 0.22 18.68 ± 2.41 2.27 ± 0.17

C32 589.4 [C32 fatty acid + 109Ag]+ 0.80 ± 0.10 4.25 ± 0.68 2.41 ± 0.24


Unknown 625.5 [Unk-B2 + 107Ag]+ 6.42 ± 0.39 3.64 ± 0.79 -0.81 ± 0.27

669.5 [Unk-A4 + 107Ag]+ 3.33 ± 0.29 2.14 ± 0.43 -0.64 ± 0.26

108

Table 3(C) Sepal



C29 515.4 [C29 alkane + 107Ag]+ 19.28 ± 1.65 2.98 ± 0.17 -2.69 ± 0.12

C31 543.4 [C31 alkane + 107Ag]+ 11.25 ± 1.60 6.91 ± 0.14 -0.70 ± 0.17

Alcohol C26 491.3 [C26 alcohol + 109Ag]+ 1.78 ± 0.13 2.34 ± 0.14 0.39 ± 0.12

C28 519.4 [C28 alcohol + 109Ag]+ 7.64 ± 0.72 5.82 ± 0.27 -0.39 ± 0.12

C30 547.4 [C30 alcohol + 109Ag]+ 6.85 ± 0.74 11.93 ± 1.22 0.80 ± 0.18


C24 475.3 [C24 fatty acid + 107Ag]+ 2.95 ± 0.56 1.31 ± 0.13 -1.17 ± 0.26

C26 503.3 [C26 fatty acid + 107Ag]+ 4.39 ± 0.91 0.76 ± 0.05 -2.53 ± 0.26

C30 559.4 [C30 fatty acid + 107Ag]+ 4.13 ± 0.33 6.54 ± 0.88 0.66 ± 0.19


Unknown 625.5 [Unk-B2 + 107Ag]+ 4.60 ± 0.96 1.61 ± 0.29 -1.52 ± 0.33

669.5 [Unk-A4 + 107Ag]+ 2.21 ± 0.71 0.59 ± 0.13 -1.90 ± 0.47

109

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(9) McNevin, J. P.; Woodward, W.; Hannoufa, A.; Feldmann, K. A.; Lemieux, B.

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111

Figure Captions

Figure 1. Arabidopsis flower samples prepared on a LDI target plate for silver-LDI

mass spectral profiling and imaging.

Figure 2. Positive-ion mode silver-LDI mass spectrum taken from an Arabidopsis

thaliana wild-type (Ler) leaf. Mass spectra from 12674 scanning points on the

leaf were averaged. The inset is the expanded m/z range view which includes

the groups of Ag2+ peaks (triplet around m/z 215.8) and Ag3

+ peaks (quartet

around m/z 322.8). The peak at m/z 215.8 which corresponds to the ion [107Ag

+ 109Ag]+ is always the predominant peak through all mass spectra collected

under our experimental conditions.

Figure 3. Ratios of targeted cuticular wax metabolites in Arabidopsis thaliana wild-type

(Ler) and eceriferum mutant (cer2) leaves. Ratios from silver-LDI MS (left)

and GC-MS (right) analyses were scaled as log2 values. Data points in each

colored box correspond to the compound class indicated in a box. The number

of carbons is indicated for each data point. Detailed ion species assignments

and their relative intensities from silver-LDI MS and amounts from GC-MS

are listed in Table 2. Each silver-LDI MS and GC-MS analysis has 3

replicates and error bars correspond to standard errors are shown.

Figure 4. Chemically selective images of Arabidopsis thaliana wild-type (Ler) whole

flowers. The step size for data collection was set to 50 µm for both x and y

directions. Dimension of the image is 5550 µm high × 4960 µm wide. The

value in each image corresponds to the nominal m/z value of the

corresponding ions. All images were processed as normalized intensities and

112

shown as a percentage of the total ion current. All images were smoothed

linearly. Major ions detected at m/z 529 correspond to [C29 ketone + 107Ag]+.

Ions detected at m/z 515, 543 are mainly silver adduct ions of C29 and C31

alkanes. Ions at m/z 547 are from C30 alcohol, and the image for the peak at

m/z 545 corresponds to the overlapped image of C31 alkane and C30 alcohol as

[C31 alkane + 109Ag]+ and [C30 alcohol + 107Ag]+. Images for silver adduct

ions of C18:3 (at m/z 385), C26 fatty acids (at m/z 503), and an unknown

compound (at m/z 625) are also shown.

Figure 5. (A) Chemically selective images of Arabidopsis thaliana wild-type (Ler) and

cer2 mutant flowers. The step size for data collection was set to 50 µm for

both x and y directions. Dimensions of the images for Ler and cer2 are 5550

µm high × 4960 µm wide and 4100 µm high × 4770 µm wide, respectively.

C29 alkane (at m/z 515 as [C29 alkane + 107Ag]+) showed higher abundances

mainly at sepals and carpels in the wild-type than in the cer2 mutant. The

localization of C29 ketone (at m/z 529 as [C29 ketone + 107Ag]+) at the carpel

was easily recognized in the wild-type but not in the cer2 mutant. Higher

abundances of very long chain fatty acids such as C30 and C32 fatty acids (at

m/z 559 as [C30 fatty acid + 107Ag]+ and at m/z 589 as [C32 fatty acid + 109Ag]+)

were found in the cer2 mutant. (B) 3D presentations of the normalized

intensities of chemically selective images of C30 and C32 fatty acids (at m/z

559 and at m/z 589). The yellow arrows in (A) and (B) are for aligning the

viewing angle. Both fatty acids showed high abundances in the tips of petals.

C30 fatty acid showed high abundance in the carpel but C32 fatty acid did not.

113

Figure 6. Positive-ion mode silver-LDI mass spectrum taken from Arabidopsis thaliana

wild-type (Ler) and cer2 mutant flower parts, (A) carpel, (B) petal, and (C)

sepal (right). Each mass spectrum is the average of each flower part. The peak

intensities were normalized to the reference peak (m/z 215.8 which

corresponds to the ion [107Ag + 109Ag]+ ).

Figure 7. Whole flower cuticular wax profiles of Arabidopsis thaliana wild-type (Ler)

and eceriferum mutant (cer2) by GC-MS. Each bar corresponds to the amount

of a specific cuticular wax and the carbon numbers are indicated on x-axis. All

values are scaled as nmol/g fresh weight with ± standard error. Because of the

relatively high amounts of C29 alkane and ketone, they were scaled by a factor

of 0.2 and 0.1, respectively. For values that exceed the y-axis range, the actual

y-values are indicated adjacent to the corresponding bars.

Figure 8. Ratios of targeted cuticular wax metabolites in Arabidopsis thaliana wild-type

(Ler) and eceriferum mutant (cer2) flower parts (carpel, petal, and sepal) by

silver-LDI MS and whole flowers by GC-MS. Ratios were scaled as log2

values. Data points in each colored box correspond to the compound class

indicated in the box. The number of carbons is indicated for each data point.

Detailed ion species assignments and their relative intensities for the three

flower parts were listed in Table 3. Each flower part has 5 replicates and error

bars correspond to standard errors. Whole flower analysis by GC-MS has 3

replicates and the error bars correspond to standard errors.

Figure 9. Proposed data processing scheme of silver-LDI MS data for fast, high-

throughput mutant screening. Sample plots shown were processed with

114

cuticular wax mass profiles from Arabidopsis thaliana wild-type (Ler) and

eceriferum mutant (cer2) carpels.

115

Whole Flower Imaging

Flower Parts Profiling

Figure 1.

116

300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600 620 640 660 680 700m/z

2000

4000

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8000

10000

12000

14000

16000

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Inte

nsity

322.8

363.2

365.3

517.4

503.4545.4

505.4

543.4533.4

573.5

571.5519.4475.4

599.5 627.5487.4531.4489.4 547.4

625.5597.5433.4 601.5

435.5 559.4

655.5585.5459.5 613.5 641.5669.5

200 300 400 600 800m/z

20000

40000

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nsity

322.8

215.8

Figure 2.

117

C27

C29

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C28

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C34

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Figure 3.

118

m/z529 (10%) m/z515 (5%)

m/z545 (3%) m/z547 (2%)

m/z503 (3%) m/z625 (5%)

m/z543 (3%)

m/z385 (5%)

Ler

Figure 4.

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529

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3000

2000

2000

1000

1000

00

m/z

559

(5%

)m

/z58

9 (1

%)

(A) (B

)

m/z

589

(1%

)

Figure 5.

120

200 250 300 350 400 450 500 550 600 650 700m/z

0

5

10

15

20

25

30

35

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45

50

0

5

10

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Rel

ativ

eA

bund

ance

0

5

10

15

20

25

30

35

40

45

50

531.4

529.4

533.4515.4

363.3 535.3513.4 575.4387.4

415.4 679.5601.4

363.3365.3

387.3

515.4

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627.4475.4 543.5391.4449.3 559.4 669.5585.5

517.5

545.5

363.3

547.5387.4 625.5559.5503.5

391.4 669.5433.4 583.5

Ag2+

Ag3+

Ag2+

Ag3+

Ag2+

Ag3+

Wild-type (Ler)

200 250 300 350 400 450 500 550 600 650 700m/z

0

5

10

15

20

25

30

35

40

45

50

0

5

10

15

20

25

30

35

40

45

50

0

5

10

15

20

25

30

35

40

45

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545.4531.4 561.4363.2

517.4387.3 499.3433.3 575.4 679.5650.3

363.2

365.2

559.4

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545.5587.5387.3 515.5

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545.4

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573.5515.4433.3387.3 627.4 669.5

Ag2+

Ag3+

Ag2+

Ag3+

Ag2+

Ag3+

cer2

(A) Carpel

(C) Sepal

(B) Petal

Figure 6.

121

0

50

100

150

200

C29 Ketone X 1/5 C25 C27 C29 X 1/10 C31

nmol

/g fr

esh

wei

ght

Ketone and Alkanes

Ler cer2

288 327 557 423

0

50

100

150

200

250

C18 C20 C22 C24 C26 C28 C30

nmol

/g fr

esh

wei

ght

Primary Alcohols

Ler cer2

0

50

100

150

200

C16 C18 C18:1 C18:2 C18:3 C22 C24 C26 C28 C30

nmol

/g fr

esh

wei

ght

Free fatty acids

Ler cer2 Figure 7.

122

C29

C31

C28

C30

C32

C18:3

C26

C30

C29 Ketone

-3 -2 -1 0 1 2 3

log2(cer2/Ler)

Alkane

Carpel

Fatty acid

Alcohol

C27

C29

C31

C26

C28

C30

C32

C18:3

C24

C26

C30

C32

C29 Ketone

Unk-B2

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Fatty acid

Alcohol

C16C18

C18:1

C18:2C18:3

C22

C24

C26

C28 C30

C25C27

C29C31

C18 C20C22

C24C26

C28

C30

C29 Ketone

-8 -6 -4 -2 0 2 4 6 8

log2(cer2/Ler)

Alkane

GC-MSWhole flower

Fatty acid

Alcohol

C27

C29

C31

C26

C28

C30

C18:3

C24

C26

C30

C29 Ketone

Unk-B2

Unk-A4

-3 -2 -1 0 1 2 3

log2(cer2/Ler)

Alkane

Sepal

Fatty acid

Alcohol

Figure 8.

123

MS

Raw

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350

400

450

500

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600

650

Log2 (cer2/Ler)

m/z

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/Ler

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els

-3-2-10123

350

400

450

500

550

600

650

Log2 (cer2/Ler)

m/z

cer2

/Ler

Carp

els

-3-2-10123

350

400

450

500

550

600

650

Log2 (cer2/Ler)

m/z

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513 51

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Figure 9.

124

CHAPTER 5. COLLOIDAL SILVER LASER

DESORPTION/IONIZATION MASS SPETROMETRY OF STEROLS

AND DIRECT PROBING OF CHOLESTEROL ON ASTROCYTE CELL

MONOLAYER

A paper prepared for submission to Rapid Communications in Mass Spectrometry

Sangwon Cha, Ksenija Jeftinija, Srdija Jeftinija, and Edward S. Yeung

Abstract

By using colloidal silver as a matrix, laser desorption/ionization mass spectrometric

analysis of sterols was performed. Cholesterol and phytosterols were sensitively detected as

silver adduct ions with little or no fragmentation. In-source dehydration difference depending

on hydroxyl group orientation was observed. By spraying colloidal silver homogeneously

onto the cell monolayer, cholesterol levels were probed directly from the cell monolayer

surface. Protocol for assaying relative cholesterol abundances was developed. Based on the

protocol, mass spectrometric assay of free cholesterol abundances depending on methyl beta-

cyclodextrin(MβCD) treatment time was performed and their results were compared with

results by traditional fluorometric cholesterol assay method. LDI MS protocol had simpler

sample preparation and assay steps than the traditional method. Both methods showed the

same trend of decreases in cholesterol level according to MβCD treatment time, but observed

ratios of decreases were higher in silver-LDI protocol than in enzymatic fluorometry.

125

Introduction

Cholesterol is one of major components in cell membrane and is highly localized at

lipid rafts in cell membrane. Cholesterol- and sphingolipids- rich lipid raft microdomains on

cell membrane have numerous functions including organization of neurotransmitter

signaling.1 To explore their function and associated proteins, monitoring changes of

neurotransmitters after disruption of lipid rafts is the common approach.2 Disruption of lipid

raft domain was mainly performed by inhibition of cholesterol synthesis or chemical removal

of cholesterol.2 Therefore, cholesterol level on cell membrane is a very important factor to

understand signal transduction mechanism. For chemical removal of cholesterol,

cyclodextrins which are cyclic oligosaccahrides having a lipophilic central cavity were used

for capturing cholesterol molecules.3, 4 Among those, methyl-ß-cyclodextrin (MβCD) has

known to be the most effective capturing agent for cholesterol.5 In addition, unusual

cholesterol level in diseases such as Alzheimer’s disease6 and atherosclerosis7 were found.

Therefore, probing cholesterol level on cell membrane is also important to understand

diseases.

Free cholesterol and cholesteryl esters from cultured cells are traditionally quantified

by enzymatic fluorometry.8-11 However, this fluorometric assay lacks an internal standard

which could cause miscalculation of cholesterol content.12 In addition, recovery of

cholesterol after extracting and redissolving cellular lipids in various solvents was

incomplete and the ratio of recovery also varied according to solvent compositions used.13

Chromatographic separation techniques, such as thin layer chromatography (TLC)14, gas

chromatography(GC) and high performance liquid chromatography (HPLC)15-19, have been

also utilized for measuring cholesterol amounts from cell cultures or human serum.

By combining chromatographic separation techniques with a variety of mass

spectrometric methodologies, identification as well as quantification of sterols has become

more straightforward. In addition, tandem MS have made it possible to elucidate structures of

126

sterols. GC coupled with electron impact ionization MS has been used for typical analysis of

sterols. GC-MS is sensitive and selective but chemical modification due to high temperature

analysis condition and laborious derivatization steps are disadvantageous. HPLC were

coupled with several ionization techniques. Among those, HPLC with atmospheric pressure

chemical ionization (APCI) MS is the most popular method20-22 whereas standard

electrospray ionization (ESI) method is not efficient ionization methods for sterols23.

Therefore, derivatization of sterols before spraying24 and silver ion coordinated spraying25

were demonstrated for effective ion generation through ESI in analysis of sterols and their

esters.

Differently from ionization techniques mentioned above, beam-induced ionization

techniques such as matrix-assisted laser desorption/ionization MS (MALDI MS) and

seconday ion mass spectrometry (SIMS) have been used off-line for extract analysis.

However, sensitivity of sterols in conventional MALDI MS was poor and most of sterols

were detected as dehydrated molecules which could cause losses of structural information.26

Recently, sterols were derivatized with Girad P hydrazine to Girad P hydrazones, and they

were readily detected by conventional MALDI using α-cyano-4-hydroxycinammic acid as a

matrix.27 Time-of-flight (TOF)- SIMS was also used for identification of cholesteryl ester

from HPLC lipid fractions.12 Because sample was deposited on pre-etched silver target,

cholesteryl esters were detected as silver adduct ions.12

However, beam-based techniques also have a capability of direct sampling from

intact cells or tissues. Cholesterol in animal tissues or cells was directly detected by TOF-

SIMS or MALDI MS28-31. In TOF-SIMS, surface metallization (metal enhanced-SIMS) by

silver or gold enhanced secondary ion yields and metal adduct ions of cholesterol was

predominantly detected in case of silver coating on sample surface.28, 32 By scanning through

cell or animal tissue surfaces, localization information of cholesterol was also obtained by

127

TOF-SIMS.28-30 Recently, relative quantification of cholesterol for individual cells was

successfully demonstrated by combining TOF-SIMS with in situ fluorescence microscopy.33

Recently, we first introduced aqueous silver colloidal solution as a matrix for LDI MS

of various wax compounds.34 Here we extend the use of colloidal silver matrix for analysis of

sterols inspired by silver metallization in TOF SIMS and Ag+ coordination ionspray MS. By

using a colloidal silver matrix, mass spectral profiles for sterols were obtained and in-source

dehydration patterns of them were investigated. In addition, direct probing free cholesterol

level on Astrocyte cell monolayer was performed. Free cholesterol level on cell surfaces was

manipulated by treating cell cultures with methyl-ß-cyclodextrin (MβCD). Relative

cholesterol peak intensities to the reference peak ([107Ag + 109Ag]+) were used for estimating

relative abundance of cholesterol on Astrocyte cell monolayer and results from LDI MS were

compared with those from traditional enzymatic fluorometry.


Materials and chemicals. Sterol standards were purchased from Steraloids Inc.

(Newport, RI) and plant sterol mixture was obtained from Mattrya LLC (Pleasant Gap, PA).

Colloidal suspension of silver (20 ppm) was purchased from Purest Colloids (Westhampton,

NJ). The Amplex Red Cholesterol Assay Kit was from Molecular Probes (Eugene, OR).

Earle’s Balanced Salt Solution (EBSS), Dulbecco’s Modified Eagle Medium (DMEM) high

glucose, fetal bovine serum (FBS), and trypsin (0.25%) were purchased from Invitrogen

(Carlsbad, CA). Papain was obtained from Sigma-Aldrich (St. Louis, MO). All other

chemicals were obtained from Fisher Scientific (Fairlawn, NJ).

Mass spectrometer. A Thermo Finnigan LTQ linear ion trap mass spectrometer

equipped with vMALDI source (Mountain View, CA) was used for mass spectral analysis.

nitrogen laser pulses (337 nm, maximum energy of 280 µJ/pulse, and maximum frequency of

20 Hz) were introduced through the fiber optic cable with 200µm in diameter. The laser spot

128

size on the sample plate surface was about 100 µm in diameter. The pressure of the sampling

chamber was kept at 0.17 Torr by nitrogen gas flow. All mass spectra were collected in the

positive-ion mode.

Cell culture. Mix neuron-glia cultures from neonatal rat cerebral cortex were

established as described. Cortexes from 3 newborn pups (1-3 days old) were freshly dissected

and tissues were enzymatically treated in 2 mL of papain solution (1.54 mg/mL in EBSS) for

40 min at 37 °C. After washing tissues with EBSS, tissues were treated with trypsin inhibitor

and mechanically dissociated in the DMEM medium (DMEM high glucose : heat-inactivated

FBS : penicillin/streptomycin = 89 : 10 : 1 by volume) using pipettes. Cells were plated in

the DMEM medium in culture flasks and maintained at 37 °C in a humidified 5% CO2/95%

air atmosphere. The cells were maintained by changing the medium every 2-3 days. The

cultures were then shaken overnight (12 hours)at 260 rpm at 37 °C. Cultures enriched in type

I astroglia were obtained by trypsinizing the attachedcells for 3 min. Trypsin was inactivated

by adding 3 mL of the DMEM medium. Astrocytes were plated on poly-L-lysine (100 g/mL;

MW 100,000)-coated glass coverslips or stainless steel plates. All experiments were

performed on cells that have been in culture for 1 – 3 days after re-planting.

In vitro fluorometric assay of cholesterol. Astrocyte cells were seeded in a 96-well

microplate at a density of 5 × 104 cells per well. Seeded cells were incubated in the DMEM

medium for 24 hours. The cells were treated with 100 µL of 10mM MβCD solution with

various time periods (0 to 60 minutes). After treatment, cells were washed with KPBS buffer

and cellular lipids were extracted from the cells by adding 100 µL of hexane:2-propanol (3:2,

v/v) solution. First extracts were transferred to the new 96-well microplate. The cellular

lipids were re-extracted with an additional 50 µL of hexane:2-propanol (3:2, v/v) solution

and these second extracts were transferred and merged to the first extracts. Solvents in

extracts were evaporated under vacuum and cellular lipids were resuspended in 150 µL of

phosphate buffer containing 0.1M potassium phosphate, pH 7.4, 50 mM NaCl, 5mM cholic

129

acid, and 0.1% Triton X-100 for 12 hours with shaking. Cellular free cholesterol content was

quantified by using an Amplex Red Cholesterol Assay kit (Molecular Probes, Eugene, OR)

without cholesterol esterase. Briefly, cholesterol in the cellular lipid extracts is oxidized by

cholesterol oxidase to produce H2O2. In the presence of horseradish peroxidase, 10-acetyl-

3,7-dihydoxyphenoxazine (Amplex Red) reacts with H2O2 and this reaction generates

fluorescent resorufin quantitatively. If cholesterol esterase is present, cholesterol esters can

be hydrolyzed to cholesterol. Fluorescence was measured with the fluorescence microplate

reader (Spectra Max Gemini XS, Molecular Devices, Sunnyvale, CA) using excitation at 538

nm and emission at 590 nm. Cell residues were used for cellular protein quantification by the

micro BCA protein assay kit (Pierce, Rockford, IL). The amount of cholesterol was

normalized by the amount of cellular protein.

LDI mass spectrometric assay of cholesterol. Astrocyte cells were planted on a

poly-L-lysine-coated stainless steel plate. Four spots of cell monolayer were formed on a

stainless steel plate (25 mm × 75 mm). Each spot of cell monolayer had about 5 × 104 cells in

an area of about 1.5 cm2. After planting, cells were incubated in the DMEM medium for 24

hours. The cells then were treated with MβCD solution with various time periods (0 to 60

minutes). Immediately after MβCD treatment, all cell monolayers were fixed with 4% of

paraformaldehyde solution for 30 min and transferred to KPBS buffer solution. Before

spraying colloidal silver, cell monolayers were dried under moderate vacuum (~50 Torr).

Spraying of colloidal silver solution were performed by the home-built spraying

device which is the combination of a computer-controlled syringe pump with a 500 μL

syringe (Kloehm LTD., Las Vegas, NV), MicroFlow PFA-ST nebulizer (Elemental Scientific

Inc., Omaha, NE) with a 0.25 mm i.d. sample uptake capillary, and a helium gas cylinder.

Spraying action was controlled by the supplied software “WinPump®” by Kloehm. Six sets

of spraying-drying processes were performed for each spot of cell monolayer with 100

μL/min flow rate and 12.5 μL of colloidal silver solution per spraying. Because the area

130

covered by colloidal silver on the sample plate was about 4.5 cm2 which was larger than the

spot of cell monolayer (~1.5 cm2), spraying action was performed without moving the

sample plate.

Based on optical images of cell monolayer spots which were acquired in the mass

spectrometer, rastering areas were selected and scanned with a 100 μm movement. Five laser

shots were used to obtain the mass spectrum for one scanning point. For one spot of cell

monolayer, 485 mass spectra from different scanning points were collected and then

averaged. From averaged mass spectra, intensity values of cholesterol silver adduct ion peaks

(at m/z 493.5 and 495.5) were extracted and normalized as relative intensities to the reference

peak at m/z 215.8 ([107Ag + 109Ag]+). These relative intensities were used for calculating

abundances of free cholesterol in cell monolayer. Four replicas of cell monolayers were used

for each MβCD treatment.


Silver-LDI mass spectral profiles of sterols. In silver-LDI MS, cholesterol (5-

cholesten-3β-ol) was mostly detected as silver adduct ions at m/z 493-496 and showed a

quartet of peaks with two major peaks because of the two silver isotopes ([M + 107Ag]+ at m/z

493 and [M + 109Ag]+ at m/z 495). Detection limit for cholesterol was ~ 50 pg per sample

spot. However, for high concentration of cholesterol standards (> ~50 ng/sample spot),

dehydrated cholesterol silver adduct ions ([M – H2O + Ag]+) were also detected at m/z 475-

478 with a constant laser fluence (Figure 1(a)). In Figure 1, one interesting observation was

that dehydration ions were not found in the mass spectrum of its isomer, 5-cholesten-3α-ol

(Figure 1(b)). In addition, with high laser fluence, dehydroxylated silver adduct ions ([M –

OH + Ag]+) were observed for 5-cholesten-3β-ol but not for 5-cholesten-3α-ol. This

difference could not be recognized in conventional MALDI MS because only dehydrated

ions were observed for both alpha- and beta- hydroxyl group positions. The explanation for

131

this difference in dehydroxylation or dehydration has not been reported. As shown in Figure

3, an efficient orbital overlap between beta-hydroxy and adjacent alkene group may have

stabilizing effects of the intermediates in either dehydroxyation or dehydration (Figure 2). In

addition, the other possible explanation is that beta-hydroxy and adjacent alkene group are

geometrically aligned well with the hydrogen orbital group at the allylic position and

therefore this may facilitate syn elimination of water (Figure 2).

Figure 3 shows silver-LDI mass spectrum of major phytosterol mixture. As shown in

Figure 3, sterols which are 2 Da different in molecular weight were overlapped due to two

stable silver isotopes. In other words, the peak at m/z 507 was from both [Brassicasterol + 109Ag]+ and [Campesterol + 107Ag]+. Similarly, [Stigmasterol + 109Ag]+ and [β-Sitosterol + 107Ag]+ are associated to the peak at m/z 521. However, their intensities could be individually

measured by choosing the other silver isotope adduct ion (Figure 3).

LDI mass spectrometric assay of cholesterol on cell monolayer. With colloidal

silver spraying on cell monolayer, surface cholesterol was directly probed. Silver-LDI mass

spectrum directly taken from an Astrocyte cell monolayer spot was shown in Figure 4. As

shown in Figure 4, silver adduct ions of cholesterol and dehydrated cholesterol were readily

detected at m/z 493 - 496 and at m/z 475 – 478 directly from an Astrocyte cell monolayer spot.

For obtaining mass spectral profiles directly from the cell monolayer on poly-L-lysine coated

stainless steel surface, about 20 % ~ 30 % higher laser intensity was needed compared to that

needed for standard sterol or sterol extract analysis. This may cause higher ratio of

dehydrated cholesterol ions. The peak corresponding to the silver dimer ion at m/z 215.8

([107Ag + 109Ag]+) was predominant under our silver spraying condition and this was

consistent through mass spectra from all individual scanning points on both control and

MβCD-treated cell monolayers. In addition, the relative intensities of cholesterol on one cell

monolayer with respect to the peak intensity at m/z 215.8 were consistent with a less than

10 % of relative standard deviation. Therefore, the fractional peak intensities for peaks at m/z

132

475, 477, 493, and 495 to the peak intensity at m/z 215.8 were extracted from the averaged

mass spectrum and summed for comparing relative abundances of cholesterol among cell

monolayer spots.

It should be noted that mass spectra from all scanning points showed a variation in

terms of total ion current if cell monolayer was prepared on the poly-L-lysine coated cover

slip glass. In addition, intensities from cholesterol were also about one order of magnitude

lower than those from the cell monolayer on the stainless steel plate even if 50% higher laser

intensity was used. Therefore, all cell monolayer spots were prepared on poly-L-lysine

coated stainless steel plates for obtaining relative abundance information.

Figure 5 shows relative cholesterol levels of control and MβCD-treated cell

monolayer spots which were assayed by both enzymatic fluorometry and silver-LDI MS.

From Figure 5, several features from silver-LDI MS could be summarized and compared

with enzymatic fluorometry results. First, the silver-LDI MS method successfully probed

decreased cholesterol levels on MβCD treated cell monolayer spots by estimating cholesterol

abundances with relative peak intensities. In addition, relative peak intensities of cholesterol

from four equally-treated cell monolayer spots showed less than 8 % of intensity variations.

Second, degrees of decreased cholesterol levels by MβCD treatment were found to be

consistent in independently cultured cell batch A and B by both assay methods. Third, the

silver-LDI MS method showed the larger decreases of cholesterol levels than the enzymatic

fluorometry method in the same treatment. It may be because sampling region by silver-LDI

MS is mostly limited to cell surfaces where were affected by MβCD treatment whereas

enzymatic fluorometry method probe cholesterol level from total cellular lipid extracts. This

observation may suggest that the effect of MβCD treatment on cell monolayer could be

underestimated by enzymatic fluorometry method.

133

Conclusions

LDI MS of sterols using colloidal silver as a matrix were performed and cholesterol

levels on cell monolayer spots were demonstrated. With low detection limit, cholesterol and

phytosterol standards were mainly detected as intact silver adduct ions, and a difference in

in-source dehydration between cholesterol and its isomer was observed which could not be

recognized when using conventional MALDI matrixes. By performing homogeneous and

reproducible spraying of colloidal silver solution with the micronebulizer-based spraying

device, consistent mass spectral profiles could be obtained through surfaces of Astrocyte cell

monolayer spots. Sample preparation and assay procedure of the silver-LDI MS method was

much simpler and faster than the traditional enzymatic fluorometry method because it didn’t

need any lipid extraction and enzymatic reaction step. Sampling depth by LDI-MS is thought

to be limited to the outer cell membrane surface but is still ambiguous. Further investigations

on sampling depth according to laser fluence, cell population, and planting surface

characteristics are needed.

Ackowledgement


Ames Laboratory is operated for the US Department of Energy by Iowa State University

under Contract No. W-7405-Eng-82. This work was supported by the Director of Science,

Office of Basic Energy Sciences, Divisions of Chemical Sciences and Biosciences.

134

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137

Figure Captions

Figure 1. Colloidal silver-LDI mass spectra of cholesterol (5-cholesten-3β-ol) and 5-

cholesten-3α-ol. Sample loading was 100 ng/spot for both compounds. With

the same laser intensity, dehydrated peak [M – H2O +Ag]+ was observed for

5-cholesten-3β-ol but not for 5-cholesten-3α-ol.

Figure 2. Possible explanation for the difference in in-source dehydration of 5-

cholesten-3β-ol and 5-cholesten-3α-ol.

Figure 3. Colloidal silver-LDI mass spectrum of plant sterol mixture solution. Sample

loading was 10 ng of total plant sterols/spot. Four sterol compounds were not

in equal amount in the mixture. The inset is the enlarged view of the region

m/z 500-530 where plant sterols were detected with their structures. Peaks

with the asterisk are from unknown sample plate contaminants.

Figure 4. Colloidal silver-LDI mass spectral profile directly taken from the Astrocyte

cell monolayer spot. Silver adduct ions for cholesterol and dehydrated

cholesterol were detected at m/z 493 - 496 and at m/z 475 – 478. Peaks in the

m/z 220 – 600 were magnified with factor of two. Peaks with the asterisk are

from unknown sample plate contaminants.

Figure 5. Effect of MβCD treatment on Astrocyte cells which was assayed by both

silver- LDI MS and enzymatic fluorometry method. Cholesterol levels in

silver-LDI MS were based on sum of relative intensities of peaks from

cholesterol and its fragment. Cholesterol levels in enzymatic fluorometry were

138

based on the cholesterol content which was normalized by protein content in

cells. Silver- LDI MS had 4 replicas for each treatment and enzymatic

fluorometry had 8 replicas for each treatment. Cholesterol levels were

indicated as relative abundances to the cholesterol level of control (without

MβCD treatment). Cholesterol assay were performed on two independently

cultured batches A and B. Error bars correspond to ± relative standard

deviation values.

139

450 460 470 480 490 500 510 520m/z

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85

90

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100

Rel

ativ

eAb

unda

nce

493.36

495.36

475.34 477.34

5-cholesten-3β-ol(cholesterol)

5-cholesten-3α-ol

[M + Ag]+

[M - H2O + Ag]+

(a)

(b)

Figure 1.

140

HOH H

HH

HOH H

HH

H

HO

LUMO

syn-elimination

delocalizedcarbocation

δ−

CH3H3C

5-Cholesten-3β-ol 5-Cholesten-3α-ol

Figure 2.

141

200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520m/z

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5

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[Brassicasterol + 107Ag]+

[Campesterol + 109Ag]+

[Stigmasterol + 107Ag]+

[ß-Sitosterol + 109Ag]+

505.33

523.33

521.33

519.42

509.25

507.33

HOH H

HH

HOH H

HH

HOH H

HH

HOH H

HH

Brassicasterol

Campesterol

Stigmasterol

ß-Sitosterol

Rel

ativ

eA

bund

ance

Ag2+

Ag3+

*

Figure 3.

142

200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500 520 540 560 580 600m/z

0

5

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Rel

ativ

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bund

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x2

*

*

*

*

Ag2+

Ag3+

[M + Ag]+

[M - H2O + Ag]+

234.08

309.33

421.33

391.33363.33291.33553.33

Figure 4.

143

0.0

50.0

100.0

0 min (control) 10 min 30 min

Fluorometry 100.0 78.0 67.9

Silver-LDI MS 100.0 64.6 50.0

Rela

tive

Abu

ndan

ce

Culture - A

0.0

50.0

100.0

0 min (control) 10 min 30 min

Fluorometry 100.0 76.1 70.5

Silver-LDI MS 100.0 67.0 52.5

Rela

tive

Abu

ndan

ce

Culture - B

Figure 5.

144

CHAPTER 6. GENERAL CONCLUSIONS

In this dissertation, laser desorption/ionization (LDI) mass spectrometry (MS) and

imaging mass spectrometry of small molecules was investigated with various interesting

biological systems. With use of alternative matrixes such as colloidal graphite and colloidal

silver solution, small molecules which were not detected very well with conventional

MALDI method were successfully detected.

With colloidal graphite as a matrix, cerebrosides were readily detected and imaged

from rat brain tissues whereas this class of compounds was usually suppressed in

conventional MALDI MS spectra of lipid mixture by the signals from phosphatidylcholine

species. For isobaric ions present in lipid mass spectral profiles, imaging tandem mass

spectrometry was performed and overlapped localization information was successfully

separated. In addition, GALDI MS was applied to plant materials such as fruit samples and

Arabidopsis thaliana plants which is one of the most important plant models. Various classes

of secondary metabolites such as small organic acids, oligosaccharides, long chain fatty acids,

and flavonoids were detected with high sensitivity. Especially, by imaging of Arabidopsis

flower petals, the heterogeneous distribution of flavonoid species in a single flower organ

was discovered for the first time by GALDI imaging MS. This discovery has a possibility of

expanding understandings of functional genomics studies of the flavonoid biosynthetic

pathway.

With colloidal silver matrix, cuticular wax compounds were directly profiled and

imaged from Arabidopsis thaliana flower surfaces. This wax metabolite profiling of flower

parts has never been studied by the traditional GC-MS protocol. Reproducible mass profiles

from both wild-type and mutants were obtained by using the homogeneous colloidal silver

spraying technique. Comparison of relative abundances of wax compounds through wild-

type and mutants by silver LDI MS provided the idea of mutant gene product functions in

145

wax biosynthesis pathway and showed good agreement with traditional GC-MS results. In

addition, cholesterol levels were directly probed from Asctrocyte cell monolayers by using

silver LDI MS.

Overall, alternative matrix-based direct profiling techniques have much simpler

sample preparation steps and shorter analysis time than extraction- and separation – based

traditional methods. Much smaller sample amount required for the analysis is also the big

advantage of direct profiling LDI MS. In addition, compared to organic acid-based MALDI

matrixes, alternative matrixes produce generally cleaner background in the low mass region

and more homogeneous sample surfaces can be generated which is suitable for imaging MS

applications. However, identification of small molecules from complete biosystems by LDI

MS is still hard to achieve for some cases and there is a high possibility of isobaric ion

overlaps in low mass region profiles. In addition, the sampling depth by LDI MS is thought

to be limited to very outer surface but still ambiguous. Therefore, further systematic studies

on separating isobaric ions based on tandem MS or high mass resolution MS or ion mobility

MS are needed, and investigation of the sampling depth according to matrix application, laser

properties, and sample materials is must.

146

APPENDIX 1. SUPPORTING FIGURES FOR CHAPTER 2

This supporting information is published online at http://pubs.acs.org*

Sangwon Cha and Edward S. Yeung

Figure Captions

Figure S-1. High-vacuum (HV)-MALDI and HV-GALDI mass spectra of standard lipid

mixtures of Batch 1. Solutions of Batch 1 are composed of a constant

concentration of total glucosylceramides (GlcCers) (0.5 mg/ml) and various

concentrations of phosphatidylcholine 32:0 (PC 32:0) (from 0.005 mg/ml to

0.25 mg/ml). Ratios on the right side of the figure represent weight ratios of

PC 32:0 to total GlcCers in each mixture. Relative abundances for the major

mass peaks are listed in Table 2.

Figure S-2. HV-MALDI and HV-GALDI mass spectra of standard lipid mixtures of Batch

2. Solutions of Batch 2 are composed of a constant concentration of PC 32:0

(0.5 mg/ml) and various concentrations of total GlcCers (from 0.005 mg/ml to


___________________________________________________________________________

* http://pubs3.acs.org/acs/journals/supporting_information.page?in_manuscript=ac062251h


147

PC 32:0 and total GlcCers in each mixture. Relative abundances for the major


Figure S-3. Intermediate pressure (IP)-MALDI and IP-GALDI mass spectra of standard

lipid mixtures of Batch 1. Solutions of Batch 1 are composed of a constant

concentration of total GlcCers (0.5 mg/ml) and various concentrations of PC

32:0 (from 0.005 mg/ml to 0.25 mg/ml). Ratios on the right side of the figure

represent weight ratios of PC 32:0 to total GlcCers in each mixture. Relative

abundances for the major mass peaks are listed in Table 2.

Figure S-4. IP-MALDI and IP-GALDI mass spectra of standard lipid mixtures of Batch 2.

Solutions of Batch 2 are composed of the constant concentration of PC 32:0

(0.5 mg/ml) and various concentrations of total GlcCers (from 0.005 mg/ml to


PC 32:0 and total GlcCers in each mixture. Relative abundances for major


Figure S-5. Mass spectrum of rat brain tissue in the negative-ion mode. This mass

spectrum is the average of mass spectra from all rastering points (10,817

points) on the rat brain tissue.

Figure S-6. First generation product ion spectra of ions at m/z 844.50. NL 59, NL 124, NL

183, and NL 256 could correspond to the loss of trimethylamine, ethyl

phosphate, phosphocholine head group, and palmitic acid from [PC 38:6 +

K]+, respectively. NL 43, NL 284, and NL 304 could correspond to the loss of

148

aziridine, stearic acid (18:0), and arachidonic acid (20:4) from [PE 38:4 + 2K

– H]+, respectively.

149

HV HIDLAM- V IDLAG- reCclG:CP s

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4:1

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Figure S- 1.

150

HV HIDLAM- V IDLAG- reCclG:CP s

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1:4

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Figure S- 2.

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APPENDIX 2. DIRECT PROFILING AND MS IMAGING OF SMALL

METABOLITES FROM FRUITES BY COLLOIDAL GRAPHITE-

ASSISTED LASER DESORPTION/IONIZATION MASS

SPECTROMETRY

A paper published in Analytical Chemistry*

Hui Zhang, Sangwon Cha, Edward S. Yeung

Abstract

Due to a high background in the low mass region, conventional MALDI is not as

useful for detecting small molecules (molecular weights < 500 Da) as it is for large ones.

Also, spatial inhomogeneity that is inherent to crystalline matrixes can degrade resolution in

imaging mass spectrometry (IMS). In this study, colloidal graphite was investigated as an

alternative matrix for laser desorption/ionization (GALDI) in IMS. We demonstrate its

advantages over conventional MALDI in the detection of small molecules such as organic

acids, flavonoids and oligosaccharides. GALDI provides good sensitivity for such small

molecules. The detection limit of fatty acids and flavonoids in negative ion mode are in low

femtomoles range. Molecules were detected directly and identified by comparing the MS and

MS/MS spectra with those of standards. Various fruits were chosen to evaluate the practical

utility of GALDI since many types of small molecules are present in them. Distribution of

these small molecules in the fruit was investigated by using IMS and IMS/MS.

___________________________________________________________________________

* Reprint with permission from Analytical Chemistry 2007, 79(17), 6575-6584.


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Introduction

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) has been

extensively used for the analysis of large molecules such as proteins1 and synthetic

polymers.2 The key feature of MALDI MS are its soft ionization characteristic and simplified

spectra as mostly singly charged species are generated. Compared to electrospray ionization

(ESI) MS, MALDI bears other advantages such as better tolerance to interference from salts

and buffers and simpler sample preparation. MALDI has also proven to be very useful for the

analysis of medium-size molecules (500-10 kDa) such as peptides,3 oligonucleotides,4 and

oligo-saccharides.5 However, the analysis of small molecules (< 500 Da) by conventional

MALDI MS is far less successful than that of larger molecules because the analyte ions are

strongly interfered with or are suppressed by the matrix-related ions that are predominant at

the low m/z range.

Different approaches have been employed in MALDI MS to minimize the

background in the low mass range. Reports includes derivatization of the analyte molecules

to a higher molecular weight6 or using a matrix with higher molecular weight such as

porphyrin (MW 974.6).7 Extra sample preparation was then needed, thereby limiting the

classes of analytes that can be detected. It has been observed that matrix ions can be

suppressed dramatically and sometimes complete suppression can be achieved under well

controlled conditions.8, 9 For example, surfactant additives such as cetyltrimethylammonium

bromide (CTAB) have been reported to substantially suppress the background from α-cyano-

4-hydroxycinnamic acid (CHCA).10 Laser intensity and the relative molar ratio of matrix to

analyte are the major parameters to adjust. However a suitable molar ratio is not always

achievable especially for native biological samples.

Many inorganic materials have been tested as matrixes for surface-assisted laser

desorption/ionization (SALDI), including different metal powders and metal oxide

nanoparticles such as Ag, Au, Co, Al, Mn, Mo, Zn, Sn, W, Fe3O4, SnO2, TiO2, WO3, ZnO,

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etc.11-15 Generally, those SALDI MS can provide a cleaner background than conventional

MALDI MS as no interference peaks from fragment ions of the organic matrixes were

present. Another matrix-free approach for laser desorption/ionization on porous silicon

(DIOS) was extensively studied since 1999.16, 17 Porous silicon surfaces were etched from

crystalline silicon chips with hydrofluoric acid and functionalized as the laser

desorption/ionization matrix as well as trapping agents for analyte molecules. Small

molecules including pharmaceuticals, nucleic acids, carbohydrates, and steroids were

successfully detected.18-20 In a more recent work, commercially available silicon

nanoparticles were utilized as an LDI matrix and the silicon powder preparation was

optimized for the analysis of small molecules.21 Different kinds of carbon materials,

including graphite particles,22 graphite plates,23, 24 graphite suspension in different solvents,25-

27 graphite trapped in silicone polymer,28 activated carbon powders,29 functionalized carbon

nanotubes30-33 and fullerenes,34 and more recently pencil lead,35-37 have been suggested as

alternative matrixes for LDI MS. Many kinds of analyte molecules over a wide mass range

(100-6000 Da) have been detected, such as peptides,20, 26-29, 31, 33-36 phospholipids,25

oligosaccharides,30-33, 35 fatty acids,24, 36 synthetic polymers7, 23, 26, 31, 32, 35, 37 and other various

organic compounds.7, 15, 22-29, 31, 33-37 A more detailed description of graphite-LDI can be

found in our previous paper.38 Recent reviews about small molecules MALDI MS39 and

matrix-free LDI MS can be found elsewhere.40

Imaging mass spectrometry (IMS) has proven to be a powerful technology for direct

profiling and imaging of elements and biomolecules in tissue sections. Secondary ion mass

spectrometry (SIMS),41, 42 MALDI43-47 and direct electrospray ionization (DESI)48 have been

applied as desorption/ionization techniques for the IMS of molecules such as metal elements,

peptides, proteins, lipids and other metabolites. SIMS has the best spatial resolution among

the three and DESI requires the least sample preparation and allows true in situ measurement

with the simplest instrumentation.48 The spatial resolution of MALDI IMS is in between

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SIMS and DESI IMS, usually ranging from 80-200 µm in diameter. The diverse choices of

lasers and matrixes make MALDI MS suitable for fast, simultaneous and high-throughput

analyses of metabolites from tissue samples. MALDI equipped with UV laser has been

successfully demonstrated for the imaging of peptides, proteins and lipids.43-47 Due to the

high background problem as discussed earlier there is limited application of UV-MALDI for

imaging of small molecules (< 500 Da). Infrared (IR) MALDI was introduced recently as a

technique for imaging small metabolites from fruit samples.49 Water is used as the natural

matrix for IR MALDI, but it is inevitable that the sample may dry out during the process of

IR irradiation. Different locations will thus give different sensitivities due to inhomogeneous

water content. So far, molecules that can be detected by IR MALDI are quite limited, either

because of the low desorption/ionization efficiency or low detection sensitivity. Furthermore,

the spatial resolution of IR-IMS is inherently worse than that of UV-IMS.

Previously we demonstrated that colloidal graphite was a good LDI matrix for the

analysis of molecules in 500-1000 Da range, such as different lipid species.38 This matrix

contains fine particles and is spatially homogeneous, making it suitable for quantitative

imaging. The colloidal property also allows it to be easily sprayed to form a layer on top of

tissue samples and thus simplifies imaging experiments. In this study, we investigated the

applicability of colloidal graphite as an alternative LDI matrix for the analysis of even

smaller metabolite molecules. Fruits contain many kinds of small molecules such as long-

chain fatty acids, small oligosaccharides, and flavonoids; so they serve as good systems to

test the performance. GALDI MS and tandem MS were used to identify the ionized species,

while IMS and IMS/MS were utilized to map the distribution of those molecules in fruit

slices.

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Standards such as long-chain fatty acids, oligosaccharides and flavonoids were

purchased from Sigma-Aldrich (St. Louis, MO). Dihydroxybenzoic acid (DHB) from Bruker

Daltonics (Billerica, MA) and CHCA solution from Agilent Technologies (Palo Alto, CA)

were used as standard MALDI matrixes. 2-Propanol-based colloidal graphite aerosol spray

(Aerodag G) was obtained from Acheson Colloids (Port Huron, MI). Pure water was

obtained from a MilliQ water purification system (Billerica, MA). All other chemicals were

purchased from Fisher Scientific (Fairlawn, NJ).

Apple and strawberry fruits were purchased from a local grocery store. Apple skin

was peeled off by a sharp razor blade and attached to the stainless steel plate by double-sided

tape. Apple juice was collected from crushed flesh onto a glass slide, dried and used directly.

A cryostat from International Equipment Co. (Needham Heights, MA) was used for

cryosectioning. Fruit chunks were dipped in liquid N2 before they were cryosectioned into

about 15-µm thick specimens and stored at –20 °C before mass spectrometric analysis. No

optimum cutting temperature (OCT) compounds were used to embed the fruit samples as the

interference to mass spectra from OCT compounds is known.50 Sectioned fruit slices were

directly transferred and mounted onto the stainless-steel plate. Before applying colloidal

graphite solution, the slices were dried under moderate vacuum (~50 Torr) at room

temperature for half an hour.

Long-chain fatty acid standards were prepared by dissolving stearic acid (C18, MW

284.48), pentacosanoic acid (C25, MW 382.66), hexacosanoic acid (C26, MW 396.69),

octacosanoic acid(C28, MW 424.74), and melissic acid (C30, MW 452.80) in chloroform to

a final concentration of 200 pmole/µl each. For flavonoid standards, quercetin (MW 302.24),

kaempferol (MW 286.23), phloretin (MW 274.27), and apigenin (MW 270.24) were

dissolved individually in DMSO to give concentration of 5mg/ml of each; then the four

standard solution were mixed and further diluted to a final concentration of 200 pmole/µl

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each in water/acetonitrile/trifluoroacetic acid (49.95/49.95/0.1). Oligosaccharide standards

were prepared by dissolving ribose (MW 150.13), glucose (MW 180.16), sucrose (MW

342.30), N-acetyl-D-lactosamine (LacNAc) (MW 383.35), maltotriose (MW 504.44), and

maltotetraose (MW 666.58) in water/acetonitrile/trifluoroacetic acid (49.95/49.95/0.1) to a

final concentration of 100 ng/µl each. 20 mg/mL DHB solution in 70% methanol and 30%

water (containing a 0.1% trifluoroacetic acid) was prepared. Commercial Agilent CHCA

solution at 6 mg/ml in 36/56/8 methanol/acetonitrile/water was purchased and used directly.

Four times dilution of colloidal graphite solution with 2-propanol was used for GALDI MS

and IMS.

For all mass spectrometric analysis and IMS, an LTQ linear ion trap mass

spectrometer equipped with vMALDI source (Thermo Electron, Mountain View, CA) was

used. The N2 laser (337 nm) is guided to the source by a fiber-optic cable and has a

maximum output of 280 µJ/pulse (before entering the optical fiber cable). The measured

laser spot size is ~100 µm in diameter on the sample plate surface. A more detailed

description of the LTQ with vMALDI source has been reported elsewhere.46

For conventional MALDI MS, 1 µL of DHB or CHCA matrix solution was applied

onto the stainless-steel sample plate and let to dry in air, followed by 1 µL of sample solution

on top of the matrix crystals. For GALDI MS of standards, 0.5 µL of diluted colloidal

graphite solution was applied onto the stainless-steel sample plate by a micropipette and let

to dry in air. Then 1 µL of standard solution was applied on top of the graphite spot. To

obtain mass spectra from apple juice with GALDI, 1 µl of fresh apple juice was applied onto

a dried (0.5 µl) graphite spot. For apple peels and fruit slices, diluted colloidal graphite

solution was applied by a double-action airbrush (Aztek A470 with a 0.30 mm nozzle from

Testor, Rockford, IL). The whole fruit slice was covered with colloidal graphite

homogeneously by spraying with 20 psi air pressure and 15 cm away from the sample plate

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for 30 s. Peak identification was made by comparing both mass and tandem mass spectra

with those of standards.

Optical images of fruit slices were taken inside the vMALDI source before IMS.

Serial optical images were taken every 1 mm movement of the sample stage in either x- or y-

direction. Each segment of the images has a size of 140 pixels by 170 pixels. These segments

of optical images were reconstructed as one optical image for one fruit slice. To collect mass

spectra, the same sample plate was rastered with 100 µm steps. For each raster point, a mass

spectrum was recorded for desorbed ions and integrated over 3-5 laser shots. In the cases of

IMS/MS, target precursor ions (m/z 191 or m/z 301) were first selected based on the mass

spectral profiles of strawberry. Then the first-generation product-ion spectra of the selected

precursor ion were collected from all rastering points on the strawberry slice. More laser

shots were required for MS2 experiments and so 9 laser shots were averaged for each raster

point.

Custom software “vMALDI data browser” (Version 1.0) was used to extract mass

spectra from specific locations and generate chemically selective images. This software was

provided by the instrument vendor (Thermo Electron, Mountain View, CA ). The mass

window for generating images was 0.5 Da. Intensities of the selected ion were normalized by

dividing the total ion current of each mass spectrum. Then, chemically selective images were

plotted as 3-D maps with the 3rd dimension being the normalized intensity.


MALDI and GALDI MS of Standard Mixtures of Fatty Acids, Flavonoids and

Oligosaccharides. Different classes of compounds were selected to compare the

performance of conventional MALDI and GALDI. Long-chain fatty acids (C18-C30) were

selected as one group of standards because of their important roles in many metabolic

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pathways of living organisms.51 Fatty acids can be detected by GC-MS with proper

derivatization such as esteritication to reduce the polarity and increase volatility.52 HPLC-ESI

MS can detect native fatty acids in the negative-ion mode through deprotonization.53

However, the basic pH condition which is required to produce such negative ions is not

compatible with most reverse-phase C18 columns that typically require acidic mobile phases.

To overcome this problem, judicious derivatization was needed.54 MALDI MS can eliminate

the separation step but conventional MALDI matrixes do not work well for detection due to a

high background and ion suppression in that mass region. This is underscored by the fact that

none of the selected standard fatty acids were detected with DHB or CHCA in either

positive-ion mode or negative-ion mode (data not shown). With GALDI, all five fatty acids

(100 ng each) were detected as deprotonated peaks ([M – H]–), as shown in Figure 1. It is

noteworthy that the background in the negative-ion mode of GALDI is very clean up to at

least m/z 1000 without any pretreatment. In fact, there are only a few low number carbon

cluster ions, such as C12–-C14

–; and the intensity of such peaks are much lower than those for

the analytes. GALDI is very sensitive to detect those fatty acids in negative ion mode. Fig. 2

shows the spectrum of the fatty acid mixture with sample loading of 100fmole of each on a

3mm-in-diameter spot. Such fatty acids can also be detected as potassium adduct ions ([M +

K]+) in positive ion mode (data not shown), though the detection sensitivity (detection limit:

50pmole/spot) is not as good as in negative ion mode .

Another group of standards tested were natural phenolic molecules, the flavonoids. It

was estimated that 2% of all carbon photosynthesized by plants is converted into flavonoids

or related compounds.55 They have been reported to have antioxidant, antiatherosclerotic and

anti-neurodegenerative properties, and are also known to be beneficial for the prevention of

chronic diseases like cancer and heart diseases.56, 57 In the positive-ion mode, quercetin,

kaempferol and apigenin were detected as [M + H]+ in both MALDI and GALDI

experiments (Fig. 3a-c). [M + Na]+ and [M + 2Na-H]+ ions for these three flavonoids can also

163

be detected with GALDI. Phloretin was not detected with any of the three matrixes. This

suggests that the center ring in the other three flavonoids plays an important role for

protonation. However, it was possible to detect phloretin with GALDI in the negative-ion

mode (Fig. 3f). Several peaks in the region of m/z 150-200 in the spectra were identified as

in-source-fragments for the flavonoids by using tandem MS. For example, m/z 167 was

identified as a fragment of phloretin while m/z 151 and m/z 179 were fragments of quercetin.

Unlike GALDI, which has a clean background, with DHB and CHCA, matrix peaks are

predominant and none of the four flavonoid standards were detected in the negative-ion

mode (Fig. 3d-e).With GALDI, negative ion mode provides better sensitivity for detection of

those flavonoid standards than positive ion mode does, and the detection limit are 50 fmole

and 200 fmole/3mm-in-diameter spot, respectively.

The third group of standards selected were oligosaccharides. Due to the lack of acidic

or basic groups, they are difficult to be ionized with conventional MALDI. DHB can be used

to detect large oligosaccharides (> 1000 Da)58 but smaller oligosaccharides are strongly

interfered with by matrix ions. We tested oligosaccharides between 150-700 Da with DHB

(Fig. 4a), CHCA (Fig. 4b), and graphite matrixes (Fig. 5). With CHCA, only larger

molecules like LacNAc, maltotriose and maltotetraose can be detected as [M + Na]+ but not

the smaller ones such as ribose, glucose and sucrose. DHB works slightly better than CHCA

in that the small oligosaccharides such as glucose and sucrose can be detected. However, the

intensity of the small saccharide peaks was very low. For example [ribose + Na]+ and

[glucose + Na]+ peaks are strongly suppressed as they are very close to matrix peaks [DHB +

Na]+ and [DHB + 2Na – H]+ respectively. LacNAc has the highest detection sensitivity

among all the oligosaccharides. This may suggest that the N-acetyl group has more affinity

for sodium ions than the other moieties of oligosaccharides. In both the CHCA and DHB

MALDI mass spectra (Fig. 4a-b), the matrix peaks were predominant and oligosaccharides

peaks were strongly interfered with. With GALDI, all six oligosaccharides were detected as

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[M + Na]+ with decent signal-to-noise ratios, as shown in Fig. 5. [M + Na -18]+ peaks were

also observed for all five oligosaccharides as water loss (Fig. 5). Neutral loss (NL) of 60 are

known to result from the major cross-ring cleavage fragments of oligosaccharides with 1,4

linkages.59 Here, m/z 629 and m/z 467 were observed as such fragments of maltotetraose and

maltotriose respectively. The peak at m/z 305 corresponds to the major fragment of LacNAc.

All of the above fragments were verified by tandem MS (data not shown). All cross-ring

cleavage fragments were marked with asterisks in Fig. 5. That the positive-ion mode of

GALDI gave a noisier background compared to the negative-ion mode did not prevent the

successful detection of small oligosaccharides. Small oligosaccharides such as hexose

(glucose or fructose) and sucrose can also be detected as [M – H]– under the negative-ion

mode peaks, vide infra. The detection sensitivity of oligosaccharides with GALDI under

positive ion mode is better than with GALDI under negative ion mode. For instance, the

detection limit of sucrose is 20pmole and 100pmole/3mm-in-diameter spot, respectively.

This can be understood as oligosaccharides have neither carboxyl group as fatty acids, or

aromatic rings as flavonoids which can stabilize the deprotonated phenol group.

Direct Detection of Small Metabolite Molecules from Fruit Samples. Because of

the sensitivity and background issues, GALDI in the positive-ion mode was used to detect

oligosaccharides and the negative-ion mode was used to detect other metabolite molecules

from fruit samples. Unlike experiments with the standards, colloidal graphite solution was

applied on top of the sample, otherwise the graphite particles may not be accessed by laser

irradiation. For imaging purposes, homogeneous coverage over the sample area is a must.

The application methodology has been optimized for IMS of mouse brain tissues in our

previous work38 and was used in this study without modification.

A list of small molecules detected directly from apple and strawberry samples were

summarized in Table I, with concentration data wherever available.60-65 All identifications

were made by comparing the MS spectra with those of standards. MS/MS data were also

165

compared with those of standards except those at too low a concentration to give meaningful

MS/MS data, as marked with asterisks. Tandem MS data is indispensable to identify isobaric

ions, such as m/z 191, which were observed from both apple and strawberry. Tandem mass

data of m/z 191 from apple and strawberry flesh are shown in Fig. 6. Notably, citric acid gave

a predominant product ion at m/z 111 while quinic acid has specific product ions at m/z 85,

93 and 127, as reported previously.66 By tandem MS it was confirmed that the peaks at m/z

191 were from quinic acid in apple while such peak came from citric acid in strawberry.

Fig. 7 shows typical mass spectra taken from different parts of the apple. Fruits in

supermarkets were always coated with a thin layer of wax for preservation and for better

appearance. Fatty acids are one major class of components of wax and many of those up to

C28 fatty acids were detected from apple peel, as shown in Fig. 7a. Other compounds such as

sugars or flavonoids were absent from the mass spectrum. The reason may be that such

compounds were covered by the wax layer and were not accessible. Fatty acids may be

naturally present on the apple peels as well; however, those cannot be discriminated from the

species in the artificial wax layer.

As shown in Fig. 7b, fresh apple juice gave malic acid, quinic acid, palmitic acid, and

linolenic acid in the negative-ion mode. Hexose (glucose or fructose) and sucrose were

detected as deprotonated ions as m/z 179 and m/z 341, respectively. Quercetin is one of the

major flavonoids contained in apple and it was also detected. Fig. 7c shows the spectrum in

the positive-ion mode. Sodium adduct ions of hexose and sucrose were detected, as well as

potassium adduct ions. According to the USDA nutrient database, fruits usually contain

much higher amounts of potassium than sodium (90 mg vs. 0 mg/100 g for apple and 292 mg

vs. 37 mg/100 g for strawberry).64

Fig. 7d is the representative spectrum taken from the apple core (endocarp). Here,

organic acids such as malic acid and quinic acid were still observed, but the relative

intensities were not as high as those from juice. On the other hand, higher amounts of

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flavonoids such as phloretin and quercetin accumulated in the endocarp region. Apple peel

also contains a lot of flavonoids and quercetin was the predominant one found on the inside

of apple peel (data not shown).

Fig. 8a and 8b are representative mass spectra taken from strawberry. As reported

previously with IR-MALDI,49 strawberry contains a lot of citric acid. In our study, citric acid

(m/z 191) was always the most intense peak in the negative-ion mode. GALDI can also detect

those compounds which were too low in concentration to be detected by IR-MALDI, such as

ascorbic acid and ellagic acid. Quercetin and kaempferol was also detected in the red part of

strawberry (more details in IMS data below). Other deprotonated ions include palmitic acid,

oleic acid, apigenin, hexose, and sucrose, as marked in Fig. 8a. Similar to the previous

report,49 citric acid and sucrose were barely detected in the seed region, as shown in Fig. 8b.

Instead, C16 and unsaturated C18 fatty acids were the major components.

IMS of Metabolites from Apple and Strawberry. IMS in the negative-ion mode

was performed to show the detailed distributions of different metabolite molecules on apple

and strawberry slices, as Fig. 9 and Fig. 10 respectively. Small molecules such as malic acid,

quinic acid, and sucrose distributed relatively evenly over the apple flesh part, as shown in

Fig. 9b, c, and e. Long-chain fatty acid such as linoleic acid was detected all over the slice

but more accumulated along the core line and bundles, as shown in Fig. 9d. Flavonoids also

accumulated more in the core region but not in the flesh, as shown in Fig. 9f-i. Unlike

linoleic acid, they seem to be only enriched in the bundles (both sepal and pedal), but not

along the core line. Another interesting feature is that flavonoids were found in the ventral

carpellary bundle (center of the apple slice) except for quercetin.

The images shown in Fig. 10 were scanned from a pie-shaped strawberry slice, with

the red skin on the right-hand side and one seed in the middle-right part. Citric acid, apigenin,

hexose and sucrose were distributed all over the flesh, while fatty acids such as linolenic and

linoleic acids accumulated on the seed. The peak at m/z 301.2 was detected all over the

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strawberry with a relatively constant concentration in the flesh, but showed higher local

intensity on the outside (red part) and the seed areas. The candidates were quercetin (MW

302.24) and ellagic acid (MW 302.20) and the two species could be distinguished in tandem

MS. Fig. 11a and 6b show the MS/MS spectra of ellagic acid and quercetin standards. m/z

151 and m/z 179 were specific fragments of quercetin due to the cleavage of the center ring,

as reported previously;56, 67 while ellagic acid is more rigid and only small fragments such as

NL 28 and NL 44 were observed. MS/MS product ion spectra from strawberry flesh were

similar to those from ellagic acid (Fig. 11c), while those at m/z 301.2 on the edge gave

quercetin-like fragments (Fig. 11d). The chemically selective ion image at m/z 179 with

precursor ions at m/z 301.2 is shown in Fig. 11e. The ambiguity in Fig. 10i is thus resolved.

Similarly, both citric acid (MW 192.13) and quinic acid (MW 192.17) were detected

as m/z 191 with GALDI in the negative-ion mode. IMS/MS (data not shown) with precursor

ions at m/z 191.2 showed that product ions at m/z 111.3 were detected all over the strawberry

slice, while no specific fragments of quinic acid (m/z 85 or m/z 93) were observed. This

suggests that all m/z 191 ions from strawberry were from citric acid (Fig. 10c).

Acknowledgements


Ames Laboratory is operated for the U.S. Department of Energy by Iowa State University

under Contract No. DE-AC02-07CH11358. This work was supported by the Director of

Science, Office of Basic Energy Sciences, Divisions of Chemical Sciences and Biosciences.

168

Table I. List of compounds detected directly from apple and strawberry and their average

concentrations from the literature. All species have been checked by m/z against standards,

and all but those with marked with asterisks have been checked by tandem MS.

Apple Strawberry

m/z Peaks assigned Concentrations g/Kg

m/z Peaks assigned Concentrations g/Kg

Organic acids

133 [M-H]– Malic Acid 4.9 *10-3 60 175 [M-H]– Ascorbic Acid* 0.59

191 [M-H]– Quinic Acid 0.76 *10-3 60 191 [M-H]– Citric Acid 6.9-12.6 62

255 [M-H]– Palmitic Acid 0.24 255 [M-H]– Palmitic Acid 0.12

277 [M-H]– Linolenic Acid 0.09 277 [M-H]– Linolenic Acid 0.65

279 [M-H]– Linoleic Acid 0.43 279 [M-H]– Linoleic Acid 0.90

281 [M-H]– Oleic Acid 0.07 281 [M-H]– Oleic Acid 0.42

Phenolics

273 [M-H]– Phloretin 4.7 *10-3 60 269 [M-H]– Apigenin 0.00-0.01

289 [M-H]– Epicatechin 47.1 *10-3 285 [M-H]– Kaempferol 4.6 *10-3

301 [M-H]– Quercetin 45.7 *10-3 301 [M-H]– Ellagic Acid 0.06-0.5 63

435 [M-H]– Phloridzin* 55.9 *10-3 61 301 [M-H]– Quercetin 11.4 *10-3

447 [M-H]– Quercetin Glucosides*

0.13 61 431 [M-H]– Apigenin Glucosides*

Oligo- saccharides

179 [M-H]–

203 [M+Na]+

219 [M+K]+

Glucose/ Fructose*

83.3 179 [M-H]–

203 [M+Na]+ 219 [M+K]+

Glucose/ Fructose*

44.3

341 [M-H]–

365 [M+Na]+

381 [M+K]+

Sucrose 20.7 341 [M-H]–

365 [M+Na]+ 381 [M+K]+

Sucrose

4.7

Except noted, all other concentration data come from (1) See the USDA National Nutrient

Database at http://www.nal.usda.gov/fnic/foodcomp/search/, and (2) See the USDA National

Nutrient Database at http://www.nal.usda.gov/fnic/foodcomp/Data/Flav/flav.pdf

169

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174

Figure Captions

Figure 1. Mass spectrum of fatty acid standards (C18-C30 fatty acids) with GALDI in

the negative-ion mode. Sample loading: 200 pmole of each.

Figure 2. Mass spectrum and detection limit of fatty acid standards (C18-C30 fatty

acids) with GALDI in the negative-ion mode. Sample loading: 100 fmole of

each.

Figure 3. Comparison of MALDI and GALDI spectra of flavonoid standards: quercetin

(MW 302.24), kaempferol (MW 286.23), phloretin (MW 274.27) and

apigenin (MW 270.24); Sample loading: 200 pmole of each. Apigenin,

kaempferol and quercetin were observed as [M + H]+ with DHB (a) and

CHCA (b) in the positive ion mode. With GALDI in the positive-ion mode (c),

apigenin, kaempferol and quercetin are detected as [M + H] + (m/z 271, m/z

286, and m/z 303, respectively), [M+Na] + (m/z 293, m/z 309, and m/z 325,

respectively), and [M + 2Na - H] + (m/z 315, m/z 331, and m/z 347,

respectively). Phloretin was not observed either. None of the four flavonoids

can be detected with DHB (d) or CHCA (e) in the negative ion mode;

However, all the four flavonoids are detected as [M - H]- ions with GALDI in

the negative-ion mode (f). Fragment from phloretin (m/z 167) and fragments

from quercetin (m/z 151 and m/z 179) are observed in the lower mass range as

well.

Figure 4. Mass spectrum of oligosaccharide standards with DHB (a) and CHCA (b) in

the positive-ion mode. Sample loading: 100 ng of each.

175

Figure 5. Mass spectrum of oligosaccharide standards with GALDI in the positive-ion

mode. Sample loading: 100 ng of each. Peaks with ●: water loss fragments;

peaks with *: major ring-cleavage fragments.

Figure 6. Product ion spectra of m/z 191 from (a) quinic acid standard; (b) apple flesh;

(c) citric acid standard; and (d) strawberry flesh. All spectra were collected in

the negative-ion mode.

Figure 7. Representative GALDI-MS spectra from different parts of apple. (a) fatty

acids composition on the outside of apple peel, negative-ion mode; (b) fresh

apple juice, negative-ion mode; (c) hexose and sucrose from fresh apple juice,

positive-ion mode; and (d) apple core, negative-ion mode. See Table I for

peak identification in (b) and (d).

Figure 8. Representative GALDI-MS spectra (negative-ion mode) from strawberry (a)

flesh; and (b) seed.

Figure 9. Chemically selective images of major ionic species identified from apple

endocarp region with GALDI in the negative-ion mode. (a) optical image

taken with reversed color; (b) malic acid; (c) quinic acid; (d) linoleic acid; (e)

sucrose; (f) phloretin; (g). epicatechin; (h) quercetin; and (i) phloridzin. All

peak intensities were normalized by dividing by the total ion current (TIC) of

each spectrum.

Figure 10. Chemically selective images of the major ionic species identified from

strawberry with GALDI in the negative-ion mode. (a) optical image taken

176

with reversed color. One seed was present as the darkest dot on the right-hand

side; (b) ascorbic acid; (c) citric acid; (d) linoleic acid; (e) hexose; (f) sucrose;

(g) apigenin; (h) kaempferol; and (i) m/z 301-301.5 ellagic acid + quercetin.

All peak intensities were normalized by dividing by the total ion current of

each spectrum.

Figure 11. Product ion spectra of m/z 301 from (a) ellagic acid standard; (b) strawberry

flesh; (c) quercetin standard; (d) edge of strawberry; and (e) chemically

selective image for product ion at m/z 179 (precursor ion m/z 301) of

strawberry slice with GALDI. All spectra were collected in the negative-ion

mode. The proposed fragment pathways are shown as inserts.67

177

100 150 200 250 300 350 400 450 5000

10

20

30

40

50

60

70

80

90

100

m/z

C18 Fatty Acid

C10 C13

C12C11

Rela

tive

Abu

ndan

ce (%

)

C25 Fatty Acid

C26 Fatty Acid

C28 Fatty Acid

C30 Fatty Acid

100 150 200 250 300 350 400 450 5000

10

20

30

40

50

60

70

80

90

100

m/z

C18 Fatty Acid

C10 C13

C12C11

Rela

tive

Abu

ndan

ce (%

)

C25 Fatty Acid

C26 Fatty Acid

C28 Fatty Acid

C30 Fatty Acid

Figure 1.

178

260 280 300 320 340 360 380 400 420 440 460 480 500m/z

0

10

20

30

40

50

60

70

80

90

100 283.33

395.50 423.50381.42

451.42

C25 Fatty Acid

C18 Fatty Acid

C26 Fatty Acid

C28 Fatty Acid

C30 Fatty AcidR

elat

ive

Abun

danc

e (%

)

Figure 2.

179

OHO

OH

OH

O

Apigenin

OHO

OH

OH

OH

O

Quercetin

OHO

OH

OH

OH

O

Kaempferol

OHHO

OH

OH

O

Phloretin

m/z250 290 310 380

271.42

310 320 330m/z

150 160 170 180 190 200 210 220 230 240 250 260 270 280 290 300 340 350

Rel

ativ

e A

bund

ance

361.33

287.42

339.33303.42

271.50

273.42

0

10

20

30

40

50

60

70

80

90

100

317.42

[Apigenin + H]+

[Kaempferol + H]+

[Quercetin + H]+

a.

[Kaempferol + H]+

[Quercetin + H]+

[Apigenin + H]+

287.42 303.42

379.33

271.50b.

0

10

20

30

40

50

60

70

80

90

100

+

287.33 293.33

309.33325.25 331.33

347.25

303.33

315.33

[Apigenin + H]+

[Kaempferol + H]+[Quercetin + H]+

c.

0

10

20

30

40

50

60

70

80

90

100

260 270 280 300 320 330 340 350 360 370 390 400

[Quercetin - H]-f.

188.50e.

0

10

20

30

40

50

60

70

80

90

100

153.50

315.25d.

0

10

20

30

40

50

60

70

80

90

100

[Kaempferol - H]-

[Apigenin - H]-

151.33179.33

167.33

[Phloretin - H]-

269.25

273.25

269.25

301.17

0

10

20

30

40

50

60

70

80

90

100

OHO

OH

OH

O

Apigenin

OHO

OH

OH

OH

O

Quercetin

OHO

OH

OH

OH

O

Quercetin

OHO

OH

OH

OH

O

Kaempferol

OHO

OH

OH

OH

O

Kaempferol

OHHO

OH

OH

O

Phloretin

OHHO

OH

OH

O

Phloretin

m/z250 290 310 380

271.42

310 320 330m/z

150 160 170 180 190 200 210 220 230 240 250 260 270 280 290 300 340 350150 160 170 180 190 200 210 220 230 240 250 260 270 280 290 300 340 350

Rel

ativ

e A

bund

ance

361.33

287.42

339.33303.42

271.50

273.42

0

10

20

30

40

50

60

70

80

90

100

317.42

[Apigenin + H]+

[Kaempferol + H]+

[Quercetin + H]+

a.

361.33

287.42

339.33303.42

271.50

273.42

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

317.42

[Apigenin + H]+

[Kaempferol + H]+

[Quercetin + H]+

a.

[Kaempferol + H]+

[Quercetin + H]+

[Apigenin + H]+

287.42 303.42

379.33

271.50b.

0

10

20

30

40

50

60

70

80

90

100

[Kaempferol + H]+

[Quercetin + H]+

[Apigenin + H]+

287.42 303.42

379.33

271.50b.

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

+

287.33 293.33

309.33325.25 331.33

347.25

303.33

315.33

[Apigenin + H]+


c.

0

10

20

30

40

50

60

70

80

90

100

+

287.33 293.33

309.33325.25 331.33

347.25

303.33

315.33

[Apigenin + H]+


c.

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

260 270 280 300 320 330 340 350 360 370 390 400260 270 280 300 320 330 340 350 360 370 390 400

[Quercetin - H]-f.

188.50e.

0

10

20

30

40

50

60

70

80

90

100188.50e.

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

153.50

315.25d.

0

10

20

30

40

50

60

70

80

90

100

153.50

315.25d.

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

[Kaempferol - H]-

[Apigenin - H]-

151.33179.33

167.33

[Phloretin - H]-

269.25

273.25

269.25

301.17

0

10

20

30

40

50

60

70

80

90

100

[Kaempferol - H]-

[Apigenin - H]-

151.33179.33

167.33

[Phloretin - H]-

269.25

273.25

269.25

301.17

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

Figure 3.

180

100 200 300 400 500 600m/z

LacNAC406.25 Maltotetraose

689.25

x2

0

10

20

30

40

50

60

70

80

90

100

Maltotriose527.42

Sucrose365.25

Glucose203.33

Maltotetraose689.25

Maltotriose527.42

LacNAC406.25

a.

b.

Rel

ativ

e A

bund

ance

0

10

20

30

40

50

60

70

80

90

100

100 200 300 400 500 600m/z

LacNAC406.25 Maltotetraose

689.25

x2

0

10

20

30

40

50

60

70

80

90

100

Maltotriose527.42

Sucrose365.25

Glucose203.33

Maltotetraose689.25

Maltotriose527.42

LacNAC406.25

a.

b.

Rel

ativ

e A

bund

ance

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

Figure 4.

181

100

200

300

400

500

600

700

0102030405060708090100

m/z


Rib

ose

Mal

totri

ose

LacN

Ac

Suc

rose

Glu

cose

Mal

tote

traos

e●

●●

●

●*

*

**

**

●

Figure 5.

182

5010

015

020

00102030405060708090100

m/z


173.

25

171.

3315

5.33

147.

25

127.

33

111.

50

109.

33

93.3

3

85.4

2

5010

015

020

00102030405060708090100

m/z


59.5

8

127.

33

111.

42

109.

42

93.5

0

85.5

0

71.5

0

171.

33

155.

2514

3.25

173.

25a. b.

5010

015

020

00102030405060708090100

m/z


191.

25

5010

015

020

00102030405060708090100

m/z


c. d.

111.

33

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Figure 6.

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a. Apple Peel (-)

d. Apple Endocarp (-)

c. Apple Juice (+)

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C16

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C20 C22 C24 C26 C28

447.3341.5

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[Hexose + Na] +

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Figure 7.

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Figure 8.

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Figure 9.

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Figure 10.

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Figure 11.

188

APPENDIX 3. SUPPORTING INFORMATION FOR CHAPTER 3

Sangwon Cha, Hui Zhang, Hilal I. Ilarslan, Eve Syrkin Wurtele, Libuse Brachova,

Basil J. Nikolau and Edward S. Yeung

Enhancing Spatial Resolution in Mass Spectral Imaging by ‘Oversampling’

Because 100 µm or 150 µm step size was too big to distinguish flower components—

carpels, petals, sepals and so on—and to recognize the boundaries of the flower components,

50 µm spacing was used for flower scanning. Scanning with a spacing which is smaller than

laser spot size is called oversampling. This oversampling can enhance the spatial resolution

of the chemical selective image without optical adjustments if complete ablation occurs in

each scanning spot (Jurchen et al., 2005). If complete ablation is not achieved, oversampling

just increases the number of pixels of the processed image but could not provide real

spatially-resolved chemical distribution information. The number of laser shots needed for

complete ablation was investigated experimentally by counting to when mass spectrum

started showing no or negligible signal. However, as Jurchen and coworkers pointed out

(Jurchen et al., 2005), the qualities of mass spectra collected near complete ablation point

were poor and this leads to poor sensitivities if all mass spectra collected at one point were

averaged.

To overcome this issue, ‘selective spectra averaging’ method with complete ablation

for one scanning point and ‘whole spectra averaging’ method without complete ablation for

one scanning point were performed. In selective spectra averaging, a series of mass spectra

were collected for the small area (9-16 rastering points on the sample) at one x, y coordinate

189

on the sample with a fixed number of laser shots per mass spectrum (10 laser shots in this

case) until no signal or negligible signal was observed. With an averaged number of

microscans (one microscan corresponds to getting one mass spectrum from the sample) until

complete ablation, data were collected over the sample surface. Intensity information with x,

y-coordinates for interesting m/z ranges were extracted by using the custom software from

Thermo (vMALDI Data Extract). This data were then separated to individual microscan

spectra. Under our experimental condition, 7 to 8 microscans were needed to achieve

complete ablation in most cases. For Arabidopsis flowers, averaged intensity values from the

first three to five microscans were used to generate chemically-selective images of flavonoids

and less than three microscans were averaged for the other classes of compounds. Images

from selective spectra averaging were generated by using in-house written Matlab

(Mathworks, Natick, MA, USA) program.

By using these two methods, there was no significant difference in terms of qualities

of chemical images for flavonoids but the two methods have advantages and disadvantages

over each other. Because of the need for complete ablation of graphite materials, ‘selective

spectra averaging’ method usually requires 1.3 to 2 times longer collection time compared to

‘whole spectra averaging’ method. ‘Whole spectra averaging’ method can reduce the data

collection time but there is a possibility of resulting in poor image quality if the sample

contains many different surface properties that can lead to different ion yields, or if

interesting molecules have very different ionization characteristics or different abundances.

These possible problems can be resolved in ‘selective spectra averaging’ method by varying

number of microscans to be averaged according to different ion species. For example, the ion

species at m/z 717 on stigma depleted much quicker than flavonoid species. Therefore, if the

number of microscans averaged for ions at m/z 717 are the same as the number of those for

flavonoid species, chemical distribution information of m/z 717 becomes indistinguishable

from the background. Figure S2 shows chemically-selective images from Arabidopsis

190

thaliana flower by using ‘selective spectra averaging’ method. When comparing chemically

selective images for ions at m/z 717 (Figure 7 and Figure S2), it is obvious that clearer

background was generated by selective spectra averaging method.

Jurchen, J.C., Rubakhin, S.S. and Sweedler, J.V. (2005) MALDI-MS Imaging of Features

Smaller than the Size of the Laser Beam. Journal of the American Society for Mass

Spectrometry, 16, 1654-1659.

191

Figure Captions

Figure S-1. Chemically selective images of ions at m/z 194, 210, and 226 and GALDI

mass spectrum of chloroform-dipped area. The mass spectrum was averaged

from 10 scanning points.

Figure S-2. Chemically-selective images of Arabidopsis flowers. Data were collected by

‘selective averaging’ method described in experimental procedure section.

The step size for data collection was set to 50 µm for both x and y directions.

Dimension of the images is 4700 µm high × 6700 µm wide. Chemical

compositions of corresponding m/z values were listed in Table 1. All images

were processed with absolute intensity values except the three mass images

for m/z 421, 451, and 978, which were processed with normalized intensities.

The maximum intensity value is listed under each image. For the image of

ions at m/z 717, the first two microscans were averaged for image presentation.

For the rest of the images, the first five microscans were averaged.

192

m/z 194 (-16) m/z 210 m/z 226 (+16) leaf1_30s_bottom_TI #6937-6946 RT: 97.53-97.67 AV: 10 NL: 2.96E4T: ITMS - c MALDI Full ms [150.00-1000.00]

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473.42 517.42301.35 545.44445.38559.39403.34325.30 373.32 429.33 587.40

615.40 643.37 669.35 689.29 721.31 771.39

Figure S-1.

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Figure S-2.

194

ACKNOWLEDGEMENT

First of all, I would like to thank my advisor, Professor Edward S. Yeung for the

generous support through my graduate works. I really enjoyed working with him and I have

learned a lot in all aspects. I sincerely admire him for his enthusiasm, dedication, and insight

to research. He is a great mentor and scientist.

I am also grateful to my POS committee members, Dr. Robert Houk, Dr. Victor Lin,

Dr. Basil Nikolau, Dr. Srdija Jeftinija, and Dr. Hans Stauffer for their precious advices and

supports.

I want thank all current and past Dr. Yeung group members for their help, advices,

and friendship: Becky Li, Melissa Zhang, Aoshuang Xu, Wei Sun, Wenjun Xie, Dr. Ning

Fang, Dr. Jiyoung Lee, Guoxin Lu, Slavica Isailovic, Dr. Frank Li, Dr. Dragan Isailovic, Dr.

Hungwing Li, Dr. Bob Hsin, and Dr. Seongho Kang. I specially thank to the mass

spectrometry project team, Dr. Hui Zhang and Dr. Chanan Sluszny. I really enjoyed working

with them. Besides our group members, my coworkers, Dr. Zhihong Song, Dr. Wenxu Zhou,

Dr. Libuse Brachova, and Dr. Ksenia Jeftinija deserve thanks for their direct assistance to my

research. In addition, I thank to my friends, Jeongyun Choi for helping Matlab programming

and Dr. Insik Jeon for precious comments.

I would like to thank all my friends for their support and happy moments we’ve

shared in Ames. Finally, I want to express my gratitude and love to my parents and all

families for their love, endless support, advices and… everything. Specially thanks to my

wife, Sang-Hee Shim for her support and love. You complete me.

laser desorption/ionization mass spectrometry for direct

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